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youngboy12's Projects

3dunetcnn icon 3dunetcnn

Keras 3D U-Net Convolution Neural Network (CNN) designed for medical image segmentation

cam icon cam

Class Activation Mapping

deeplearning-500-questions icon deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，近30万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

dlinterview icon dlinterview

Deep Learning Interview 深度学习面试题目汇总

ensemble-objdet icon ensemble-objdet

A basic ensemble method for object detection. Given bounding boxes from multiple object detectors, output a single cohesive set of bounding boxes.

h-denseunet icon h-denseunet

TMI 2018. H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT Volumes

iciar2018 icon iciar2018

Two-Stage Convolutional Neural Network for Breast Cancer Histology Image Classification. ICIAR 2018 Grand Challenge on BreAst Cancer Histology images (BACH)

impersonator icon impersonator

PyTorch implementation of our ICCV 2019 paper: Liquid Warping GAN: A Unified Framework for Human Motion Imitation, Appearance Transfer and Novel View Synthesis

l-gm-loss icon l-gm-loss

Implementation of our accepted CVPR 2018 paper "Rethinking Feature Distribution for Loss Functions in Image Classification"

maskrcnn-benchmark icon maskrcnn-benchmark

Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.

pretrained-models.pytorch icon pretrained-models.pytorch

Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.

pumpkin-book icon pumpkin-book

《机器学习》（西瓜书）公式推导解析，在线阅读地址：https://datawhalechina.github.io/pumpkin-book

pwc icon pwc

Papers with code. Sorted by stars. Updated weekly.

torch-cam icon torch-cam

Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM)

viscnn_cvpr_2016_loc icon viscnn_cvpr_2016_loc

A PyTorch implementation of paper "Learning Deep Features for Discriminative Localization"

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