Keras Paper Implementations Papers Implementations Aggregated Residual Transformations for Deep Neural Networks Implementation An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Implementation U-Net: Convolutional Networks for Biomedical Image Segmentation Implementation Distilling the Knowledge in a Neural Network Implementation SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size Implementation A fully automated deep learning-based network for detecting COVID-19 from a new and large lung CT scan dataset Implementation V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation Implementation UNETR: Transformers for 3D Medical Image Segmentation Implementation DoRA: Weight-Decomposed Low-Rank Adaptation Implementation Improved Deep Metric Learning with Multi-class N-pair Loss Objective Implementation RoFormer: Enhanced Transformer with Rotary Position Embedding Implementation
