Stars
An end-to-end walkthrough with a custom object detection pipeline for face detection!
Mohan259 / U-2-Net_myself
Forked from xuebinqin/U-2-NetThe code for our newly accepted paper in Pattern Recognition 2020: "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection."
For practicing Tensorflow and other DL projects
Leetcode solutions by Neetcode YT
[TMM-2023] Official implementation of "Towards Complete and Detail-Preserved Salient Object Detection", A.K.A [Arxiv] SelfReformer
PyTorch Tutorials from my YouTube channel
A Pytorch Knowledge Distillation library for benchmarking and extending works in the domains of Knowledge Distillation, Pruning, and Quantization.
A PyTorch implementation for exploring deep and shallow knowledge distillation (KD) experiments with flexibility
A general framework for knowledge distillation
Model Compression Based on Geoffery Hinton's Logit Regression Method in Keras applied to MNIST 16x compression over 0.95 percent accuracy.An Implementation of "Distilling the Knowledge in a Neural …
A coding-free framework built on PyTorch for reproducible deep learning studies. PyTorch Ecosystem. 🏆26 knowledge distillation methods presented at TPAMI, CVPR, ICLR, ECCV, NeurIPS, ICCV, AAAI, etc…
EasyNLP: A Comprehensive and Easy-to-use NLP Toolkit
Awesome Knowledge Distillation
This repo is developed for evaluating binary image segmentation results. Measures, such as MAE, Precision, Recall, F-measure, PR curves and F-measure curves are included.
Code for CVPR 2019 paper. BASNet: Boundary-Aware Salient Object Detection
This is the repo for our new project Highly Accurate Dichotomous Image Segmentation
A technical report on convolution arithmetic in the context of deep learning
The code for our newly accepted paper in Pattern Recognition 2020: "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection."
https://www.youtube.com/channel/UC34rW-HtPJulxr5wp2Xa04w?sub_confirmation=1
Blog https://medium.com/neuralmachine/knowledge-distillation-dc241d7c2322
A resource for learning about Machine learning & Deep Learning

