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Web Application + Flower classification using transfer learning on the dataset obtained from http://www.robots.ox.ac.uk/~vgg/data/flowers/102/
The Markdown-based note-taking app that doesn't suck.
PyTorch implementation for "Gated Transfer Network for Transfer Learning"
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
Windows Precision Touchpad Driver Implementation for Apple MacBook / Magic Trackpad
A treasure chest for visual classification and recognition powered by PaddlePaddle
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，50余万字。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
Principal Feature Visualization for convolutional neural networks
手把手撕LeetCode题目，扒各种算法套路的裤子。English version supported! Crack LeetCode, not only how, but also why.
The repository includes texture representation, recognition, segmentation and others of texture analysis.
(ImageNet pretrained models) The official pytorch implemention of the TPAMI paper "Res2Net: A New Multi-scale Backbone Architecture"
Pytorch implementation of RetinaNet object detection.
The implementation of "Towards accurate one-stage object detection with AP-loss".
This repository contains the code implementation used in the paper "Multi-species Seagrass Detection and Classification from Underwater Images"
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition (https://arxiv.org/pdf/2006.11538.pdf)
Pytorch implementation of Feature Pyramid Network (FPN) for Object Detection
Feature Pyramid Networks for Object Detection
Train the HRNet model on ImageNet
A PyTorch implementation of EfficientNet
A pytorch implementation of Deep Residual Network for Steganalysis of Digital Images (SRNet)
VIP cheatsheets for Stanford's CS 229 Machine Learning
手写实现李航《统计学习方法》书中全部算法
Implementing MixNet: Mixed Depthwise Convolutional Kernels using Pytorch