QuSophia's Stars
pengsida/learning_research
本人的科研经验
phecy/SSL-FEW-SHOT
SSL-FEW-SHOT
zhanyuanyang/fsc-cl
stoneloong/fish_recognition
海洋鱼类识别系统
tee-lab/schooling_fish
This repository contains codes and data used in the research article "Noise-Induced Schooling of Fish" (https://doi.org/10.1038/s41567-020-0787-y). Currently to use any material on this repository please contact Jitesh Jhawar (jiteshjhawar@gmail.com)
ahsan856jalal/Fish-Abundance
Fish detection in unconstrained environment
andrewssobral/bgslibrary
A C++ Background Subtraction Library with wrappers for Python, MATLAB, Java and GUI on QT
OutBreak-hui/YoloV5-Flexible-and-Inference
基于YoloV5的一些魔改及相关部署方案
microsoft/Cream
This is a collection of our NAS and Vision Transformer work.
kevin-ssy/FishNet
Implementation code of the paper: FishNet: A Versatile Backbone for Image, Region, and Pixel Level Prediction, NeurIPS 2018
wenweixu/keras-yolo3
Training and Detecting Objects with YOLO3 for underwater fish
IssamLaradji/affinity_lcfcn
agrija9/ssl-sonar-images
Code for our paper Self-supervised Learning for Sonar Image Classification [CVPR 2022]
wyharveychen/CloserLookFewShot
source code to ICLR'19, 'A Closer Look at Few-shot Classification'
labmlai/annotated_deep_learning_paper_implementations
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
AyanKumarBhunia/DIY-FSCIL
[CVPR-2022] ''Doodle It Yourself: Class Incremental Learning by Drawing a Few Sketches'', IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2022.
MRZHANG-1997/Python
UnderwaterDL/AdvFish
Code for paper "Large-scale Underwater Fish Recognition via Deep Adversarial Learning"
ahsan856jalal/Fish-detection-and-classification-using-HOGY
This algorithm detects and classifies fish instances under unconstrained environment using a hybrid of GMM, Optical flow and deep CNN based on YOLO . Preference is given to YOLO during hybridization when results from GMM-optical and YOLO are overlapping
kennethleungty/Neural-Network-Architecture-Diagrams
Diagrams for visualizing neural network architecture (Created with diagrams.net)
NVlabs/FAN
Official PyTorch implementation of Fully Attentional Networks