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mengkunzhao's Projects

computer-vision-in-action icon computer-vision-in-action

《计算机视觉实战演练:算法与应用》中文电子书、源码、读者交流社区(持续更新中 ...) 📘 在线电子书 https://charmve.github.io/computer-vision-in-action/ 👇项目主页

confgcn icon confgcn

AISTATS 2019: Confidence-based Graph Convolutional Networks for Semi-Supervised Learning

conv-caps-hsi-classification icon conv-caps-hsi-classification

Code for the paper "Deep Convolutional Capsule Network for Hyperspectral Image Spectral and Spectral-Spatial Classification"

conv_arithmetic icon conv_arithmetic

A technical report on convolution arithmetic in the context of deep learning

ctspine1k icon ctspine1k

A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography

cvpr2019 icon cvpr2019

cvpr2019/cvpr2018/cvpr2019 papers,极市团队整理

dassl.pytorch icon dassl.pytorch

A PyTorch toolbox for domain adaptation and semi-supervised learning.

data_augmentation_zoo_for_object_detection icon data_augmentation_zoo_for_object_detection

Includes: Learning data augmentation strategies for object detection | GridMask data augmentation | Augmentation for small object detection in Numpy. Use RetinaNet with ResNet-18 to test these methods on VOC and KITTI.

ddfnet icon ddfnet

The official implementation of the CVPR2021 paper: Decoupled Dynamic Filter Networks

deep-high-resolution-net.pytorch icon deep-high-resolution-net.pytorch

The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"

deepbrainseg icon deepbrainseg

Fully automatic brain tumour segmentation using Deep 3-D convolutional neural networks

deepcluster icon deepcluster

Deep Clustering for Unsupervised Learning of Visual Features

deephyperx icon deephyperx

Deep learning toolbox based on PyTorch for hyperspectral data classification.

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

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