flyccccchild's starred repositories
tensorflow
An Open Source Machine Learning Framework for Everyone
segment-anything
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
ultralytics
NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite
nndl.github.io
《神经网络与深度学习》 邱锡鹏著 Neural Network and Deep Learning
albumentations
Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
deep_learning_object_detection
A paper list of object detection using deep learning.
Yet-Another-EfficientDet-Pytorch
The pytorch re-implement of the official efficientdet with SOTA performance in real time and pretrained weights.
fcn.berkeleyvision.org
Fully Convolutional Networks for Semantic Segmentation by Jonathan Long*, Evan Shelhamer*, and Trevor Darrell. CVPR 2015 and PAMI 2016.
awesome-lane-detection
A paper list of lane detection.
awesome-semantic-segmentation-pytorch
Semantic Segmentation on PyTorch (include FCN, PSPNet, Deeplabv3, Deeplabv3+, DANet, DenseASPP, BiSeNet, EncNet, DUNet, ICNet, ENet, OCNet, CCNet, PSANet, CGNet, ESPNet, LEDNet, DFANet)
awesome-anomaly-detection
A curated list of awesome anomaly detection resources
data-science-competition
该仓库用于记录作者本人参加的各大数据科学竞赛的获奖方案源码以及一些新比赛的原创baseline. 主要涵盖:kaggle, 阿里天池,华为云大赛校园赛,百度aistudio,和鲸社区,datafountain等
FCN.tensorflow
Tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation (http://fcn.berkeleyvision.org)
Efficient-Segmentation-Networks
Lightweight models for real-time semantic segmentationon PyTorch (include SQNet, LinkNet, SegNet, UNet, ENet, ERFNet, EDANet, ESPNet, ESPNetv2, LEDNet, ESNet, FSSNet, CGNet, DABNet, Fast-SCNN, ContextNet, FPENet, etc.)
PyTorch-ENet
PyTorch implementation of ENet
complexNetworksMeasurements
Algorithms to measure some networks characteristics like robustness and fractality
awesome-autonomous-vehicle-resource
一份关于无人驾驶汽车的资源列表(中文版)