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aerial-object-detector

To develop a object detection system for aerial data

aerialdetection

autodl-projects

Automated deep learning algorithms implemented in PyTorch.

awesome-pruning

A curated list of neural network pruning resources.

channel-pruning

Channel Pruning for Accelerating Very Deep Neural Networks (ICCV'17)

deep-neuroevolution

Deep Neuroevolution

deepcompression-pytorch

Learning both Weights and Connections for Efficient Neural Networks https://arxiv.org/abs/1506.02626

detection-pytorch-notebook

代码 -《深度学习之PyTorch物体检测实战》

faster-rcnn.pytorch

A faster pytorch implementation of faster r-cnn

faster_rcnn

Faster R-CNN

filter-pruning-geometric-median

Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration (CVPR 2019 Oral)

gan-pruning

A Pytorch implementation of "Co-Evolutionary Compression for Unpaired Image Translation" (ICCV 2019).

google-access-helper

谷歌访问助手破解版

leetcode

LeetCode Solutions: A Record of My Problem Solving Journey.( leetcode题解，记录自己的leetcode解题之路。)

leetcode-1

Python & JAVA Solutions for Leetcode

lihang-code

《统计学习方法》的代码实现

metapruning

mmdetection

Open MMLab Detection Toolbox and Benchmark

model-compression

model compression based on pytorch (1、quantization: 16/8/4/2 bits(dorefa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、ternary/binary value(twn/bnn/xnor-net)；2、 pruning: normal、regular and group convolutional channel pruning；3、 group convolution structure；4、batch-normalization folding for quantization)

models

Models and examples built with TensorFlow

multi-objective-genetic-algorithm-meta-optimization

network-slimming

Network Slimming (Pytorch) (ICCV 2017)

neural-network-genetic-algorithm

Evolving a neural network with a genetic algorithm.

nsga-ii

This is a python implementation of NSGA-II algorithm. NSGA is a popular non-domination based genetic algorithm for multi-objective optimization. It is a very effective algorithm but has been generally criticized for its computational complexity, lack of elitism and for choosing the optimal parameter value for sharing parameter σshare. A modified version, NSGA II was developed, which has a better sorting algorithm , incorporates elitism and no sharing parameter needs to be chosen a priori.

nsga-ii-1

The implementation of NSGA-II with Python

nsga-iii

NSGA-III, A-NSGA-III, and A^2-NSGA-III algorithms based on Kanpur Genetic Algorithms Laboratory's code. They solve Multi-objective Optimization Problems (MOPs) and Many-objective Optimization Problems (MaOPs) with constraints (Real and binary decision variables).

nsga-net

NSGA-Net, a Neural Architecture Search Algorithm

nsga2

Non Sorting Genetic Algorithm II

once-for-all

[ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment

paddleslim

PaddleSlim is an open-source library for deep model compression and architecture search.