[
  {
    "Top-1 accuracy %": 8.4,
    "code_links": [
      {
        "title": "Boyiliee/MoEx",
        "url": "https://github.com/Boyiliee/MoEx"
      }
    ],
    "date": "2020-02-25",
    "date2": 20200225,
    "model": "CutMix+MoEx (ResNet-50)",
    "paper": {
      "title": "On Feature Normalization and Data Augmentation",
      "url": "https://cknow.io/lib/97886b7d4f78b45f"
    },
    "paper_data_uoa": "97886b7d4f78b45f"
  },
  {
    "Top-1 accuracy %": 7.3,
    "code_links": [
      {
        "title": "rwightman/pytorch-image-models",
        "url": "https://github.com/rwightman/pytorch-image-models"
      },
      {
        "title": "clovaai/CutMix-PyTorch",
        "url": "https://github.com/clovaai/CutMix-PyTorch"
      },
      {
        "title": "ildoonet/cutmix",
        "url": "https://github.com/ildoonet/cutmix"
      },
      {
        "title": "hysts/pytorch_cutmix",
        "url": "https://github.com/hysts/pytorch_cutmix"
      },
      {
        "title": "DevBruce/CutMixImageDataGenerator_For_Keras",
        "url": "https://github.com/DevBruce/CutMixImageDataGenerator_For_Keras"
      },
      {
        "title": "kboseong/RotNet",
        "url": "https://github.com/kboseong/RotNet"
      },
      {
        "title": "airplane2230/keras_cutmix",
        "url": "https://github.com/airplane2230/keras_cutmix"
      },
      {
        "title": "SyogoShibuya/Chainer-Cutmix",
        "url": "https://github.com/SyogoShibuya/Chainer-Cutmix"
      },
      {
        "title": "toshi-k/kaggle-bengaliai-handwritten-grapheme-classification",
        "url": "https://github.com/toshi-k/kaggle-bengaliai-handwritten-grapheme-classification"
      },
      {
        "title": "Bennie-Han/Image-augementation-pytorch",
        "url": "https://github.com/Bennie-Han/Image-augementation-pytorch"
      }
    ],
    "date": "2019-05-13",
    "date2": 20190513,
    "model": "CutMix (ResNet-50)",
    "paper": {
      "title": "CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features",
      "url": "https://cknow.io/lib/434d13ec994a62b3"
    },
    "paper_data_uoa": "434d13ec994a62b3"
  },
  {
    "Top-1 accuracy %": 6.6,
    "code_links": [
      {
        "title": "rwightman/pytorch-image-models",
        "url": "https://github.com/rwightman/pytorch-image-models"
      },
      {
        "title": "facebookresearch/mixup-cifar10",
        "url": "https://github.com/facebookresearch/mixup-cifar10"
      },
      {
        "title": "hongyi-zhang/mixup",
        "url": "https://github.com/hongyi-zhang/mixup"
      },
      {
        "title": "david8862/keras-YOLOv3-model-set",
        "url": "https://github.com/david8862/keras-YOLOv3-model-set"
      },
      {
        "title": "lRomul/argus-freesound",
        "url": "https://github.com/lRomul/argus-freesound"
      },
      {
        "title": "hongyi-zhang/Fixup",
        "url": "https://github.com/hongyi-zhang/Fixup"
      },
      {
        "title": "tugstugi/pytorch-speech-commands",
        "url": "https://github.com/tugstugi/pytorch-speech-commands"
      },
      {
        "title": "JunweiLiang/Object_Detection_Tracking",
        "url": "https://github.com/JunweiLiang/Object_Detection_Tracking"
      },
      {
        "title": "scut-aitcm/Competitive-Inner-Imaging-SENet",
        "url": "https://github.com/scut-aitcm/Competitive-Inner-Imaging-SENet"
      },
      {
        "title": "scut-aitcm/CompetitiveSENet",
        "url": "https://github.com/scut-aitcm/CompetitiveSENet"
      },
      {
        "title": "simongrest/farm-pin-crop-detection-challenge",
        "url": "https://github.com/simongrest/farm-pin-crop-detection-challenge"
      },
      {
        "title": "P2333/Mixup-Inference",
        "url": "https://github.com/P2333/Mixup-Inference"
      },
      {
        "title": "rit-git/Snippext_public",
        "url": "https://github.com/rit-git/Snippext_public"
      },
      {
        "title": "jonnor/datascience-master",
        "url": "https://github.com/jonnor/datascience-master"
      },
      {
        "title": "yell/kaggle-camera",
        "url": "https://github.com/yell/kaggle-camera"
      },
      {
        "title": "simongrest/kaggle-freesound-audio-tagging-2019",
        "url": "https://github.com/simongrest/kaggle-freesound-audio-tagging-2019"
      },
      {
        "title": "jianshen92/stanford-car-grab-challenge",
        "url": "https://github.com/jianshen92/stanford-car-grab-challenge"
      },
      {
        "title": "tanmaypandey7/wheat-detection",
        "url": "https://github.com/tanmaypandey7/wheat-detection"
      },
      {
        "title": "AngusG/bn-advex-zhang-fixup",
        "url": "https://github.com/AngusG/bn-advex-zhang-fixup"
      },
      {
        "title": "amerch/CIFAR100-Training",
        "url": "https://github.com/amerch/CIFAR100-Training"
      },
      {
        "title": "transcendentsky/mixup",
        "url": "https://github.com/transcendentsky/mixup"
      },
      {
        "title": "makeyourownmaker/mixup",
        "url": "https://github.com/makeyourownmaker/mixup"
      },
      {
        "title": "jmaronas/calibration_MixupDNN_ARCLoss.pytorch",
        "url": "https://github.com/jmaronas/calibration_MixupDNN_ARCLoss.pytorch"
      },
      {
        "title": "OFRIN/Tensorflow_MixUp",
        "url": "https://github.com/OFRIN/Tensorflow_MixUp"
      },
      {
        "title": "toshi-k/kaggle-bengaliai-handwritten-grapheme-classification",
        "url": "https://github.com/toshi-k/kaggle-bengaliai-handwritten-grapheme-classification"
      },
      {
        "title": "akjgskwi/mixup_chainer",
        "url": "https://github.com/akjgskwi/mixup_chainer"
      },
      {
        "title": "teang1995/satellite_image_task",
        "url": "https://github.com/teang1995/satellite_image_task"
      },
      {
        "title": "Bennie-Han/Image-augementation-pytorch",
        "url": "https://github.com/Bennie-Han/Image-augementation-pytorch"
      },
      {
        "title": "CaoShuning/MIXUP",
        "url": "https://github.com/CaoShuning/MIXUP"
      },
      {
        "title": "Taoudi/DataAugmentation",
        "url": "https://github.com/Taoudi/DataAugmentation"
      }
    ],
    "date": "2017-10-25",
    "date2": 20171025,
    "model": "Mixup (ResNet-50)",
    "paper": {
      "title": "mixup: Beyond Empirical Risk Minimization",
      "url": "https://cknow.io/lib/ed03044f9b3c9a7f"
    },
    "paper_data_uoa": "ed03044f9b3c9a7f"
  },
  {
    "Top-1 accuracy %": 4.4,
    "code_links": [
      {
        "title": "uoguelph-mlrg/Cutout",
        "url": "https://github.com/uoguelph-mlrg/Cutout"
      },
      {
        "title": "barisozmen/deepaugment",
        "url": "https://github.com/barisozmen/deepaugment"
      },
      {
        "title": "khanrc/pt.fractalnet",
        "url": "https://github.com/khanrc/pt.fractalnet"
      },
      {
        "title": "etetteh/sota-data-augmentation-and-optimizers",
        "url": "https://github.com/etetteh/sota-data-augmentation-and-optimizers"
      },
      {
        "title": "Ximilar-com/tf-image",
        "url": "https://github.com/Ximilar-com/tf-image"
      },
      {
        "title": "LMaxence/Cifar10_Classification",
        "url": "https://github.com/LMaxence/Cifar10_Classification"
      },
      {
        "title": "YaCpotato/B4ResearchDeepaugment",
        "url": "https://github.com/YaCpotato/B4ResearchDeepaugment"
      },
      {
        "title": "dishen12/Cuout_modify",
        "url": "https://github.com/dishen12/Cuout_modify"
      },
      {
        "title": "sour4bh/cifar-10",
        "url": "https://github.com/sour4bh/cifar-10"
      }
    ],
    "date": "2017-08-15",
    "date2": 20170815,
    "model": "Cutout (ResNet-50)",
    "paper": {
      "title": "Improved Regularization of Convolutional Neural Networks with Cutout",
      "url": "https://cknow.io/lib/5776e75da4897869"
    },
    "paper_data_uoa": "5776e75da4897869"
  },
  {
    "Top-1 accuracy %": 4.2,
    "code_links": [
      {
        "title": "tensorflow/models",
        "url": "https://github.com/tensorflow/models/tree/master/research/slim"
      },
      {
        "title": "tensorflow/models",
        "url": "https://github.com/tensorflow/models/tree/master/research/deeplab"
      },
      {
        "title": "tensorflow/models",
        "url": "https://github.com/tensorflow/models"
      },
      {
        "title": "fastai/fastai",
        "url": "https://github.com/fastai/fastai"
      },
      {
        "title": "pytorch/vision",
        "url": "https://github.com/pytorch/vision"
      },
      {
        "title": "fchollet/deep-learning-models",
        "url": "https://github.com/fchollet/deep-learning-models"
      },
      {
        "title": "tensorpack/tensorpack",
        "url": "https://github.com/tensorpack/tensorpack"
      },
      {
        "title": "tensorpack/tensorpack",
        "url": "https://github.com/tensorpack/tensorpack/tree/master/examples/ResNet"
      },
      {
        "title": "KaimingHe/deep-residual-networks",
        "url": "https://github.com/KaimingHe/deep-residual-networks"
      },
      {
        "title": "facebook/fb.resnet.torch",
        "url": "https://github.com/facebook/fb.resnet.torch"
      },
      {
        "title": "facebookarchive/fb.resnet.torch",
        "url": "https://github.com/facebookarchive/fb.resnet.torch"
      },
      {
        "title": "osmr/imgclsmob",
        "url": "https://github.com/osmr/imgclsmob"
      },
      {
        "title": "keras-team/keras-applications",
        "url": "https://github.com/keras-team/keras-applications"
      },
      {
        "title": "ry/tensorflow-resnet",
        "url": "https://github.com/ry/tensorflow-resnet"
      },
      {
        "title": "qubvel/efficientnet",
        "url": "https://github.com/qubvel/efficientnet"
      },
      {
        "title": "facebookresearch/pycls",
        "url": "https://github.com/facebookresearch/pycls"
      },
      {
        "title": "raghakot/keras-resnet",
        "url": "https://github.com/raghakot/keras-resnet"
      },
      {
        "title": "mbadry1/Top-Deep-Learning",
        "url": "https://github.com/mbadry1/Top-Deep-Learning"
      },
      {
        "title": "google/flax",
        "url": "https://github.com/google/flax/tree/master/examples/imagenet"
      },
      {
        "title": "wenxinxu/resnet-in-tensorflow",
        "url": "https://github.com/wenxinxu/resnet-in-tensorflow"
      },
      {
        "title": "deepmind/dm-haiku",
        "url": "https://github.com/deepmind/dm-haiku"
      },
      {
        "title": "researchmm/SiamDW",
        "url": "https://github.com/researchmm/SiamDW"
      },
      {
        "title": "gcr/torch-residual-networks",
        "url": "https://github.com/gcr/torch-residual-networks"
      },
      {
        "title": "NVIDIA/retinanet-examples",
        "url": "https://github.com/NVIDIA/retinanet-examples"
      },
      {
        "title": "D-X-Y/ResNeXt-DenseNet",
        "url": "https://github.com/D-X-Y/ResNeXt-DenseNet"
      },
      {
        "title": "glouppe/info8010-deep-learning",
        "url": "https://github.com/glouppe/info8010-deep-learning"
      },
      {
        "title": "akamaster/pytorch_resnet_cifar10",
        "url": "https://github.com/akamaster/pytorch_resnet_cifar10"
      },
      {
        "title": "xiaoyufenfei/LEDNet",
        "url": "https://github.com/xiaoyufenfei/LEDNet"
      },
      {
        "title": "DeepMark/deepmark",
        "url": "https://github.com/DeepMark/deepmark"
      },
      {
        "title": "itijyou/ademxapp",
        "url": "https://github.com/itijyou/ademxapp"
      },
      {
        "title": "andreasveit/densenet-pytorch",
        "url": "https://github.com/andreasveit/densenet-pytorch"
      },
      {
        "title": "yxgeee/MMT",
        "url": "https://github.com/yxgeee/MMT"
      },
      {
        "title": "deepmodeling/deepmd-kit",
        "url": "https://github.com/deepmodeling/deepmd-kit"
      },
      {
        "title": "kwotsin/TensorFlow-ENet",
        "url": "https://github.com/kwotsin/TensorFlow-ENet"
      },
      {
        "title": "amusi/daily-question",
        "url": "https://github.com/amusi/daily-question"
      },
      {
        "title": "bentrevett/pytorch-image-classification",
        "url": "https://github.com/bentrevett/pytorch-image-classification"
      },
      {
        "title": "OlafenwaMoses/IdenProf",
        "url": "https://github.com/OlafenwaMoses/IdenProf"
      },
      {
        "title": "GKalliatakis/Keras-VGG16-places365",
        "url": "https://github.com/GKalliatakis/Keras-VGG16-places365"
      },
      {
        "title": "hongyi-zhang/Fixup",
        "url": "https://github.com/hongyi-zhang/Fixup"
      },
      {
        "title": "alrojo/lasagne_residual_network",
        "url": "https://github.com/alrojo/lasagne_residual_network"
      },
      {
        "title": "rtanno21609/AdaptiveNeuralTrees",
        "url": "https://github.com/rtanno21609/AdaptiveNeuralTrees"
      },
      {
        "title": "facebookresearch/stochastic_gradient_push",
        "url": "https://github.com/facebookresearch/stochastic_gradient_push"
      },
      {
        "title": "OlafenwaMoses/Traffic-Net",
        "url": "https://github.com/OlafenwaMoses/Traffic-Net"
      },
      {
        "title": "calmisential/TensorFlow2.0_ResNet",
        "url": "https://github.com/calmisential/TensorFlow2.0_ResNet"
      },
      {
        "title": "peteryuX/arcface-tf2",
        "url": "https://github.com/peteryuX/arcface-tf2"
      },
      {
        "title": "CUHK-MMLAB/polynet",
        "url": "https://github.com/CUHK-MMLAB/polynet"
      },
      {
        "title": "YudeWang/UNet-Satellite-Image-Segmentation",
        "url": "https://github.com/YudeWang/UNet-Satellite-Image-Segmentation"
      },
      {
        "title": "mingxingtan/efficientnet",
        "url": "https://github.com/mingxingtan/efficientnet"
      },
      {
        "title": "makatx/YOLO_ResNet",
        "url": "https://github.com/makatx/YOLO_ResNet"
      },
      {
        "title": "hycis/TensorGraph",
        "url": "https://github.com/hycis/TensorGraph"
      },
      {
        "title": "oskyhn/CNNs-Without-Borders",
        "url": "https://github.com/oskyhn/CNNs-Without-Borders"
      },
      {
        "title": "mhagiwara/nanigonet",
        "url": "https://github.com/mhagiwara/nanigonet"
      },
      {
        "title": "chrhenning/hypercl",
        "url": "https://github.com/chrhenning/hypercl"
      },
      {
        "title": "thughost2/Padam",
        "url": "https://github.com/thughost2/Padam"
      },
      {
        "title": "OlafenwaMoses/Action-Net",
        "url": "https://github.com/OlafenwaMoses/Action-Net"
      },
      {
        "title": "CVxTz/face_age_gender",
        "url": "https://github.com/CVxTz/face_age_gender"
      },
      {
        "title": "uclaml/Padam",
        "url": "https://github.com/uclaml/Padam"
      },
      {
        "title": "ChangweiZhang/Awesome-WindowsML-ONNX-Models",
        "url": "https://github.com/ChangweiZhang/Awesome-WindowsML-ONNX-Models"
      },
      {
        "title": "MishaLaskin/vqvae",
        "url": "https://github.com/MishaLaskin/vqvae"
      },
      {
        "title": "nitinvwaran/UrbanSound8K-audio-classification-with-ResNet",
        "url": "https://github.com/nitinvwaran/UrbanSound8K-audio-classification-with-ResNet"
      },
      {
        "title": "MishaLaskin/vq-vae",
        "url": "https://github.com/MishaLaskin/vq-vae"
      },
      {
        "title": "vlievin/Unet",
        "url": "https://github.com/vlievin/Unet"
      },
      {
        "title": "marload/ConvNets-TensorFlow2",
        "url": "https://github.com/marload/ConvNets-TensorFlow2"
      },
      {
        "title": "km1414/CNN-models",
        "url": "https://github.com/km1414/CNN-models"
      },
      {
        "title": "aby2s/sharpmask",
        "url": "https://github.com/aby2s/sharpmask"
      },
      {
        "title": "XDF2018/ML_Embedded_Workshop",
        "url": "https://github.com/XDF2018/ML_Embedded_Workshop"
      },
      {
        "title": "anguyen8/sam",
        "url": "https://github.com/anguyen8/sam"
      },
      {
        "title": "DableUTeeF/keras-efficientnet",
        "url": "https://github.com/DableUTeeF/keras-efficientnet"
      },
      {
        "title": "koshian2/ResNet-MultipleFramework",
        "url": "https://github.com/koshian2/ResNet-MultipleFramework"
      },
      {
        "title": "DaikiTanak/manifold_mixup",
        "url": "https://github.com/DaikiTanak/manifold_mixup"
      },
      {
        "title": "Masao-Taketani/FOTS_OCR",
        "url": "https://github.com/Masao-Taketani/FOTS_OCR"
      },
      {
        "title": "anibali/dsnt-pose2d",
        "url": "https://github.com/anibali/dsnt-pose2d"
      },
      {
        "title": "Dohppak/Music_Genre_Classification",
        "url": "https://github.com/Dohppak/Music_Genre_Classification"
      },
      {
        "title": "hysts/pytorch_resnet",
        "url": "https://github.com/hysts/pytorch_resnet"
      },
      {
        "title": "rajneeshaggarwal/google-efficientnet",
        "url": "https://github.com/rajneeshaggarwal/google-efficientnet"
      },
      {
        "title": "isheunesutembo/TB-Computer-Aided-Diagnosis-Using-Deep-Learning",
        "url": "https://github.com/isheunesutembo/TB-Computer-Aided-Diagnosis-Using-Deep-Learning"
      },
      {
        "title": "shtnkgm/VisionFrameworkSample",
        "url": "https://github.com/shtnkgm/VisionFrameworkSample"
      },
      {
        "title": "asprenger/keras_fc_densenet",
        "url": "https://github.com/asprenger/keras_fc_densenet"
      },
      {
        "title": "varshaneya/Res-SE-Net",
        "url": "https://github.com/varshaneya/Res-SE-Net"
      },
      {
        "title": "Graylab/deepH3-distances-orientations",
        "url": "https://github.com/Graylab/deepH3-distances-orientations"
      },
      {
        "title": "iArunava/ResNet",
        "url": "https://github.com/iArunava/ResNet"
      },
      {
        "title": "swasun/VQ-VAE-images",
        "url": "https://github.com/swasun/VQ-VAE-images"
      },
      {
        "title": "Lornatang/ResNet-PyTorch",
        "url": "https://github.com/Lornatang/ResNet-PyTorch"
      },
      {
        "title": "wuqiyao20160118/mini_project-for-CIFAR10",
        "url": "https://github.com/wuqiyao20160118/mini_project-for-CIFAR10"
      },
      {
        "title": "ajithvallabai/getsetgo_keras-beginner",
        "url": "https://github.com/ajithvallabai/getsetgo_keras-beginner"
      },
      {
        "title": "deontaepharr/Residual-Attention-Network",
        "url": "https://github.com/deontaepharr/Residual-Attention-Network"
      },
      {
        "title": "lixixibj/tsImage-forecasting",
        "url": "https://github.com/lixixibj/tsImage-forecasting"
      },
      {
        "title": "lixixibj/forecasting-with-time-series-imaging",
        "url": "https://github.com/lixixibj/forecasting-with-time-series-imaging"
      },
      {
        "title": "patientzero/timage-icann2019",
        "url": "https://github.com/patientzero/timage-icann2019"
      },
      {
        "title": "fabiofumarola/ultrayolo",
        "url": "https://github.com/fabiofumarola/ultrayolo"
      },
      {
        "title": "jimheaton/Ultra96_ML_Embedded_Workshop",
        "url": "https://github.com/jimheaton/Ultra96_ML_Embedded_Workshop"
      },
      {
        "title": "MichaelWangfc/distributed-tensorflow-resnet",
        "url": "https://github.com/MichaelWangfc/distributed-tensorflow-resnet"
      },
      {
        "title": "hysts/pytorch_resnet_preact",
        "url": "https://github.com/hysts/pytorch_resnet_preact"
      },
      {
        "title": "jtcass01/SIMON",
        "url": "https://github.com/jtcass01/SIMON"
      },
      {
        "title": "Baichenjia/Resnet",
        "url": "https://github.com/Baichenjia/Resnet"
      },
      {
        "title": "Punakshi/Deep-Residual-Learning-for-Image-Recognition-Implementation",
        "url": "https://github.com/Punakshi/Deep-Residual-Learning-for-Image-Recognition-Implementation"
      },
      {
        "title": "lab-midas/med_segmentation",
        "url": "https://github.com/lab-midas/med_segmentation"
      },
      {
        "title": "alalagong/LEDNet",
        "url": "https://github.com/alalagong/LEDNet"
      },
      {
        "title": "EdenMelaku/Transfer-Learning-Pytorch-Implmentation",
        "url": "https://github.com/EdenMelaku/Transfer-Learning-Pytorch-Implmentation"
      },
      {
        "title": "luanshiyinyang/ResNet",
        "url": "https://github.com/luanshiyinyang/ResNet"
      },
      {
        "title": "hyperrixel/cheXrad",
        "url": "https://github.com/hyperrixel/cheXrad"
      },
      {
        "title": "b8goal/PIRL-Residual-network",
        "url": "https://github.com/b8goal/PIRL-Residual-network"
      },
      {
        "title": "EdenMelaku/Transfer-Learning-Pytorch-Implementation",
        "url": "https://github.com/EdenMelaku/Transfer-Learning-Pytorch-Implementation"
      },
      {
        "title": "danielamassiceti/CCA-visualdialogue",
        "url": "https://github.com/danielamassiceti/CCA-visualdialogue"
      },
      {
        "title": "fengredrum/cnn-xla",
        "url": "https://github.com/fengredrum/cnn-xla"
      },
      {
        "title": "pikkaay/efficientnet_gpu",
        "url": "https://github.com/pikkaay/efficientnet_gpu"
      },
      {
        "title": "usnistgov/image-classification-resnet50",
        "url": "https://github.com/usnistgov/image-classification-resnet50"
      },
      {
        "title": "seyrankhademi/ResNet_CIFAR10",
        "url": "https://github.com/seyrankhademi/ResNet_CIFAR10"
      },
      {
        "title": "anoushkrit/Knowledge",
        "url": "https://github.com/anoushkrit/Knowledge"
      },
      {
        "title": "nellopai/deepLearningModels",
        "url": "https://github.com/nellopai/deepLearningModels"
      },
      {
        "title": "EstherBear/implementation-of-pruning-filters",
        "url": "https://github.com/EstherBear/implementation-of-pruning-filters"
      },
      {
        "title": "AngusG/bn-advex-zhang-fixup",
        "url": "https://github.com/AngusG/bn-advex-zhang-fixup"
      },
      {
        "title": "greatsharma/DeepLearning-Papers-Implementation",
        "url": "https://github.com/greatsharma/DeepLearning-Papers-Implementation"
      },
      {
        "title": "brycexu/MR-Residual-Net",
        "url": "https://github.com/brycexu/MR-Residual-Net"
      },
      {
        "title": "sebsquire/FlowersRecognition_keras",
        "url": "https://github.com/sebsquire/FlowersRecognition_keras"
      },
      {
        "title": "serre-lab/gala_tpu",
        "url": "https://github.com/serre-lab/gala_tpu"
      },
      {
        "title": "icepoint666/itsumo-cv",
        "url": "https://github.com/icepoint666/itsumo-cv"
      },
      {
        "title": "hershd23/ObjectLocalizer",
        "url": "https://github.com/hershd23/ObjectLocalizer"
      },
      {
        "title": "Glp91/fire-detection",
        "url": "https://github.com/Glp91/fire-detection"
      },
      {
        "title": "JONGSKY/paper",
        "url": "https://github.com/JONGSKY/paper"
      },
      {
        "title": "shoji9x9/Fashion-MNIST-By-ResNet",
        "url": "https://github.com/shoji9x9/Fashion-MNIST-By-ResNet"
      },
      {
        "title": "angelvillar96/FaceEmoji",
        "url": "https://github.com/angelvillar96/FaceEmoji"
      },
      {
        "title": "shoji9x9/CIFAR-10-By-small-ResNet",
        "url": "https://github.com/shoji9x9/CIFAR-10-By-small-ResNet"
      },
      {
        "title": "usnistgov/image-regression-resnet50",
        "url": "https://github.com/usnistgov/image-regression-resnet50"
      },
      {
        "title": "shoaibahmed/CrossLayerPooling",
        "url": "https://github.com/shoaibahmed/CrossLayerPooling"
      },
      {
        "title": "northeastsquare/effficientnet",
        "url": "https://github.com/northeastsquare/effficientnet"
      },
      {
        "title": "James-Gilbert-/medical-deep-learning",
        "url": "https://github.com/James-Gilbert-/medical-deep-learning"
      },
      {
        "title": "nsom/VGG16",
        "url": "https://github.com/nsom/VGG16"
      },
      {
        "title": "Thehunk1206/Covid-19-covidcnn",
        "url": "https://github.com/Thehunk1206/Covid-19-covidcnn"
      },
      {
        "title": "KarimaCha/CNN_Trust_Prediction",
        "url": "https://github.com/KarimaCha/CNN_Trust_Prediction"
      },
      {
        "title": "LuigiRussoDev/Covid19Detection",
        "url": "https://github.com/LuigiRussoDev/Covid19Detection"
      },
      {
        "title": "sebsquire/Dogs-and-cats-image-classification-CNN",
        "url": "https://github.com/sebsquire/Dogs-and-cats-image-classification-CNN"
      },
      {
        "title": "akommini/Spoken-Numeric-Digit-detection",
        "url": "https://github.com/akommini/Spoken-Numeric-Digit-detection"
      },
      {
        "title": "xinkuansong/modified-resnet-acc-0.9638-10.7M-parameters",
        "url": "https://github.com/xinkuansong/modified-resnet-acc-0.9638-10.7M-parameters"
      },
      {
        "title": "xcmyz/Face-Binary-Classification",
        "url": "https://github.com/xcmyz/Face-Binary-Classification"
      },
      {
        "title": "nsom/Basic-Models",
        "url": "https://github.com/nsom/Basic-Models"
      },
      {
        "title": "XinlueLiu/TensorFlow-classifiers",
        "url": "https://github.com/XinlueLiu/TensorFlow-classifiers"
      },
      {
        "title": "Rakshit-Shetty/Resnet-Implementation",
        "url": "https://github.com/Rakshit-Shetty/Resnet-Implementation"
      },
      {
        "title": "demul/ResidualNet",
        "url": "https://github.com/demul/ResidualNet"
      },
      {
        "title": "realmichaelye/Skin-Lesions-Classifier-ResNet50",
        "url": "https://github.com/realmichaelye/Skin-Lesions-Classifier-ResNet50"
      },
      {
        "title": "xcmyz/FaceDetection",
        "url": "https://github.com/xcmyz/FaceDetection"
      },
      {
        "title": "julik43/IIMAS-USCS",
        "url": "https://github.com/julik43/IIMAS-USCS"
      },
      {
        "title": "Thehunk1206/Covid-19-chest-X-ray",
        "url": "https://github.com/Thehunk1206/Covid-19-chest-X-ray"
      },
      {
        "title": "mminamina/Transfer_Learning_ResNet18---Keypoints_Detection",
        "url": "https://github.com/mminamina/Transfer_Learning_ResNet18---Keypoints_Detection"
      },
      {
        "title": "leemathew1998/RG",
        "url": "https://github.com/leemathew1998/RG"
      },
      {
        "title": "phillity/BioCapsule",
        "url": "https://github.com/phillity/BioCapsule"
      },
      {
        "title": "Jeongyun-Lee-0423/Classification",
        "url": "https://github.com/Jeongyun-Lee-0423/Classification"
      },
      {
        "title": "FranckZibi/SharpNet",
        "url": "https://github.com/FranckZibi/SharpNet"
      },
      {
        "title": "cairachel9/diabetic",
        "url": "https://github.com/cairachel9/diabetic"
      },
      {
        "title": "CodeChefVIT/VOID",
        "url": "https://github.com/CodeChefVIT/VOID"
      },
      {
        "title": "xcmyz/Face_Binary_Classfication",
        "url": "https://github.com/xcmyz/Face_Binary_Classfication"
      },
      {
        "title": "mminamina/Transfer_Learning_NaimishNet---Keypoints_Detection",
        "url": "https://github.com/mminamina/Transfer_Learning_NaimishNet---Keypoints_Detection"
      },
      {
        "title": "JesonZhang822/Dogs-VS-Cats-Project",
        "url": "https://github.com/JesonZhang822/Dogs-VS-Cats-Project"
      },
      {
        "title": "sammyamajumdar/ResNet50",
        "url": "https://github.com/sammyamajumdar/ResNet50"
      },
      {
        "title": "kaseris/ILSVRCPlus",
        "url": "https://github.com/kaseris/ILSVRCPlus"
      },
      {
        "title": "gundeep15/SCD_AI_Project",
        "url": "https://github.com/gundeep15/SCD_AI_Project"
      },
      {
        "title": "astoycos/Mini_Project2",
        "url": "https://github.com/astoycos/Mini_Project2"
      },
      {
        "title": "t0930198/backup",
        "url": "https://github.com/t0930198/backup"
      },
      {
        "title": "dssbxx/k_labels_resnet50",
        "url": "https://github.com/dssbxx/k_labels_resnet50"
      },
      {
        "title": "leemathew1998/GradientWeight",
        "url": "https://github.com/leemathew1998/GradientWeight"
      },
      {
        "title": "matakshay/Neural_Image_Caption_Generator",
        "url": "https://github.com/matakshay/Neural_Image_Caption_Generator"
      },
      {
        "title": "ferhatkkochan/pneumonia_classifier",
        "url": "https://github.com/ferhatkkochan/pneumonia_classifier"
      },
      {
        "title": "tazzaoui/capgen",
        "url": "https://github.com/tazzaoui/capgen"
      },
      {
        "title": "saloni1998/Cifar-10",
        "url": "https://github.com/saloni1998/Cifar-10"
      },
      {
        "title": "wonjaek36/sodeep_final",
        "url": "https://github.com/wonjaek36/sodeep_final"
      },
      {
        "title": "UnofficialJuliaMirror/DeepMark-deepmark",
        "url": "https://github.com/UnofficialJuliaMirror/DeepMark-deepmark"
      },
      {
        "title": "MaxwellHeller/coffee_fraud_detection",
        "url": "https://github.com/MaxwellHeller/coffee_fraud_detection"
      },
      {
        "title": "c1ph3rr/Deep-Residual-Learning-for-Image-Recognition",
        "url": "https://github.com/c1ph3rr/Deep-Residual-Learning-for-Image-Recognition"
      },
      {
        "title": "rickyHong/tfRecord-Caltech256-repl2",
        "url": "https://github.com/rickyHong/tfRecord-Caltech256-repl2"
      },
      {
        "title": "bclwan/MRI_Brain_Segmentation",
        "url": "https://github.com/bclwan/MRI_Brain_Segmentation"
      },
      {
        "title": "Sangkwun/Resnet",
        "url": "https://github.com/Sangkwun/Resnet"
      },
      {
        "title": "anjandeepsahni/face_recognition",
        "url": "https://github.com/anjandeepsahni/face_recognition"
      },
      {
        "title": "Zachdr1/CNNs",
        "url": "https://github.com/Zachdr1/CNNs"
      },
      {
        "title": "suhas1999/Flip-kart-grid-challenge",
        "url": "https://github.com/suhas1999/Flip-kart-grid-challenge"
      },
      {
        "title": "akar5h/Image-Recognition-with-CNN-and-Transfer-Learning-ResNet101",
        "url": "https://github.com/akar5h/Image-Recognition-with-CNN-and-Transfer-Learning-ResNet101"
      },
      {
        "title": "gatheluck/Stronghold",
        "url": "https://github.com/gatheluck/Stronghold"
      },
      {
        "title": "kimchigame/image-classfication-Resnet",
        "url": "https://github.com/kimchigame/image-classfication-Resnet"
      },
      {
        "title": "EricEntrup/reference",
        "url": "https://github.com/EricEntrup/reference"
      },
      {
        "title": "yangboz/TransferLearning4Dentist",
        "url": "https://github.com/yangboz/TransferLearning4Dentist"
      },
      {
        "title": "Scott-S-Lin/DL-example",
        "url": "https://github.com/Scott-S-Lin/DL-example"
      },
      {
        "title": "CrossEntropy/Gesture-images-recognition-ResidualNetwork",
        "url": "https://github.com/CrossEntropy/Gesture-images-recognition-ResidualNetwork"
      },
      {
        "title": "sanoyo/dl-model",
        "url": "https://github.com/sanoyo/dl-model"
      },
      {
        "title": "OoO256/cifar10-resnet",
        "url": "https://github.com/OoO256/cifar10-resnet"
      },
      {
        "title": "CanshangD/ResNet_tensorflow2.0",
        "url": "https://github.com/CanshangD/ResNet_tensorflow2.0"
      },
      {
        "title": "HarshaVardhanVanama/Cheat-Sheets-and-Links",
        "url": "https://github.com/HarshaVardhanVanama/Cheat-Sheets-and-Links"
      },
      {
        "title": "zjZSTU/ResNet",
        "url": "https://github.com/zjZSTU/ResNet"
      },
      {
        "title": "anjandeepsahni/face_classification",
        "url": "https://github.com/anjandeepsahni/face_classification"
      },
      {
        "title": "xhlulu/arxiv-assistant",
        "url": "https://github.com/xhlulu/arxiv-assistant"
      },
      {
        "title": "eric-erki/IdenProf",
        "url": "https://github.com/eric-erki/IdenProf"
      },
      {
        "title": "jiajunhua/facebookresearch-Detectron",
        "url": "https://github.com/jiajunhua/facebookresearch-Detectron"
      },
      {
        "title": "horse007666/ResNet",
        "url": "https://github.com/horse007666/ResNet"
      },
      {
        "title": "bluein/BCCD-Project",
        "url": "https://github.com/bluein/BCCD-Project"
      },
      {
        "title": "ewinata/CIFAR-10",
        "url": "https://github.com/ewinata/CIFAR-10"
      },
      {
        "title": "TowardHumanizedInteraction/TripletFace",
        "url": "https://github.com/TowardHumanizedInteraction/TripletFace"
      },
      {
        "title": "danielparada1/RL_SpaceInvaders",
        "url": "https://github.com/danielparada1/RL_SpaceInvaders"
      },
      {
        "title": "CorneliusHsiao/FoodMethodGAN",
        "url": "https://github.com/CorneliusHsiao/FoodMethodGAN"
      },
      {
        "title": "mr-bulb/DL_basic_github",
        "url": "https://github.com/mr-bulb/DL_basic_github"
      },
      {
        "title": "UnofficialJuliaMirrorSnapshots/DeepMark-deepmark",
        "url": "https://github.com/UnofficialJuliaMirrorSnapshots/DeepMark-deepmark"
      },
      {
        "title": "seansoleyman/cifar10-resnet",
        "url": "https://github.com/seansoleyman/cifar10-resnet"
      },
      {
        "title": "syiin/resnet_cancer_detection",
        "url": "https://github.com/syiin/resnet_cancer_detection"
      },
      {
        "title": "AhnYoungBin/Resnet_paper",
        "url": "https://github.com/AhnYoungBin/Resnet_paper"
      },
      {
        "title": "kiranu1024/deep-learning",
        "url": "https://github.com/kiranu1024/deep-learning"
      },
      {
        "title": "yw0nam/DenseNet",
        "url": "https://github.com/yw0nam/DenseNet"
      },
      {
        "title": "rishabmallick/Sign-language-live-predictor",
        "url": "https://github.com/rishabmallick/Sign-language-live-predictor"
      },
      {
        "title": "ankit-vaghela30/Google-landmark-prediction",
        "url": "https://github.com/ankit-vaghela30/Google-landmark-prediction"
      },
      {
        "title": "Kunaldargan/Paper-summerization--DEEP-LEARNING-MADE-EASIER-BY-LINEAR-TRANSFORMATIONS-IN-PERCEPTRONS--",
        "url": "https://github.com/Kunaldargan/Paper-summerization--DEEP-LEARNING-MADE-EASIER-BY-LINEAR-TRANSFORMATIONS-IN-PERCEPTRONS--"
      },
      {
        "title": "duchaba/Norwegian_Blue_Parrot_k2fa_AI",
        "url": "https://github.com/duchaba/Norwegian_Blue_Parrot_k2fa_AI"
      },
      {
        "title": "jday96314/Kuzushiji",
        "url": "https://github.com/jday96314/Kuzushiji"
      },
      {
        "title": "gsudllab/PaperTemplate",
        "url": "https://github.com/gsudllab/PaperTemplate"
      },
      {
        "title": "syiin/ann_cancer_detection",
        "url": "https://github.com/syiin/ann_cancer_detection"
      },
      {
        "title": "caojoshua/Plastic-Recyclability",
        "url": "https://github.com/caojoshua/Plastic-Recyclability"
      },
      {
        "title": "lixihan/Resnet",
        "url": "https://github.com/lixihan/Resnet"
      },
      {
        "title": "bertrandlalo/deep_dog_breeds",
        "url": "https://github.com/bertrandlalo/deep_dog_breeds"
      },
      {
        "title": "JHLee0513/Salt_detection_challenge",
        "url": "https://github.com/JHLee0513/Salt_detection_challenge"
      }
    ],
    "date": "2015-12-10",
    "date2": 20151210,
    "model": "ResNet-50 (300 Epochs)",
    "paper": {
      "title": "Deep Residual Learning for Image Recognition",
      "url": "https://cknow.io/lib/c67b9f49c8a43019"
    },
    "paper_data_uoa": "c67b9f49c8a43019"
  },
  {
    "Top-1 accuracy %": 2.3,
    "code_links": [
      {
        "title": "rgeirhos/texture-vs-shape",
        "url": "https://github.com/rgeirhos/texture-vs-shape"
      },
      {
        "title": "rgeirhos/Stylized-ImageNet",
        "url": "https://github.com/rgeirhos/Stylized-ImageNet"
      },
      {
        "title": "mbuet2ner/local-global-features-cnn",
        "url": "https://github.com/mbuet2ner/local-global-features-cnn"
      }
    ],
    "date": "2018-11-29",
    "date2": 20181129,
    "model": "Stylized ImageNet (ResNet-50)",
    "paper": {
      "title": "ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness",
      "url": "https://cknow.io/lib/8ffa4d6f99048eb6"
    },
    "paper_data_uoa": "8ffa4d6f99048eb6"
  },
  {
    "Top-1 accuracy %": 0,
    "code_links": [
      {
        "title": "hendrycks/natural-adv-examples",
        "url": "https://github.com/hendrycks/natural-adv-examples"
      },
      {
        "title": "oskyhn/CNNs-Without-Borders",
        "url": "https://github.com/oskyhn/CNNs-Without-Borders"
      }
    ],
    "date": "2019-07-16",
    "date2": 20190716,
    "model": "ResNet-50",
    "paper": {
      "title": "Natural Adversarial Examples",
      "url": "https://cknow.io/lib/ef65045ed6743c78"
    },
    "paper_data_uoa": "ef65045ed6743c78"
  }
]