Pinned Repositories
ad_examples
A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.
ADLR
Anomaly detection in hyperspectral images by abundance- and dictionary-based low-rank decomposition (ADLR)
Adversarially-Learned-Anomaly-Detection
ALAD (Proceedings of IEEE ICDM 2018) official code
AI-Challenger-2018-CropDisease
AI-Challenger-Plant-Disease-Recognition
AI Challenger -- 农作物病害识别
Andrew-NG-Meachine-Learning
coursera中Andrew Ng的meachine learning的所有编程测验的原文件
apollo
An open autonomous driving platform
autoware.ai
Open-source software for self-driving vehicles
awesome-cbir-papers
📝Awesome and classical image retrieval papers
Hyperspectral-Anomaly-Detection-LSUNRSORAD-and-LSAD-CR-IDW-
This is the code for the paper nemed 'Anomaly Detection for Hyperspectral Imagery Based on the Regularized Subspace Method and Collaborative Representation'
cl1314's Repositories
cl1314/Hyperspectral-Anomaly-Detection-LSUNRSORAD-and-LSAD-CR-IDW-
This is the code for the paper nemed 'Anomaly Detection for Hyperspectral Imagery Based on the Regularized Subspace Method and Collaborative Representation'
cl1314/ad_examples
A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.
cl1314/apollo
An open autonomous driving platform
cl1314/autoware.ai
Open-source software for self-driving vehicles
cl1314/awesome-earthobservation-code
curated list of awesome tools, tutorials, code, helpful projects, links, stuff about Earth Observation and Geospatial stuff!
cl1314/BASS
Bayesian Adaptive Superpixel Segmentation (ICCV 2019)
cl1314/BS-Nets-Implementation-Pytorch
BS-Nets: An End-to-End Framework For Band Selection of Hyperspectral Image
cl1314/CS-Book
计算机类常用电子书整理，并且附带下载链接，包括Java，Python，Linux，Go，C，C++，数据结构与算法，人工智能，计算机基础，面试，设计模式，数据库，前端等书籍
cl1314/Deblur-Denoising-Hyperspectral
A collection of state-of-the-art Deblur,Denoising, and Hyperspectral architectures.
cl1314/DeCNNAD
cl1314/Deep-SVDD-PyTorch
A PyTorch implementation of the Deep SVDD anomaly detection method
cl1314/DeepLearning
cl1314/DeepLearning-500-questions
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scutjy2015@163.com 版权所有，违权必究 Tan 2018.06
cl1314/Dig-into-Apollo
Apollo notes (Apollo学习笔记) - Apollo learning notes for beginners.
cl1314/flappy
An open source dynamic simulation for flapping wing robots and animals
cl1314/HSI-SVM
高光谱遥感影像识别与分类,HSI_SVM,Indian Pines
cl1314/Hyperspectral-Anomaly-Detection-2S-GLRT
This is the code of paper named "Multipixel Anomaly Detection With Unknown Patterns for Imagery"
cl1314/Hyperspectral-Anomaly-Detection-CRDBPSW
Collaborative representation with background purification and saliency weight for hyperspectral anomaly detection
cl1314/Hyperspectral-Image-Super-Resolution-Benchmark
A list of hyperspectral image super-solution resources collected by Junjun Jiang
cl1314/KITTI-Dataset
Visualising LIDAR data from KITTI dataset.
cl1314/lara2018
This repository is intended to develop the work supported by the Latin America Research Awards 2018.
cl1314/learnopencv
Learn OpenCV : C++ and Python Examples
cl1314/lrslibrary
Low-Rank and Sparse Tools for Background Modeling and Subtraction in Videos
cl1314/memae-anomaly-detection
MemAE for anomaly detection. -- Gong, Dong, et al. "Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection". ICCV 2019.
cl1314/OpenCV-Face-Recognition
Real-time face recognition project with OpenCV and Python
cl1314/PGN_anomaly_detection
Prior Generating Networks for Anomaly Detection
cl1314/PTA-HAD
a prior-based tensor approximation (PTA) is proposed for hyperspectral anomaly detection, in which HSI is decomposed into a background tensor and an anomaly tensor. In the background tensor, a low-rank prior is incorporated into spectral dimension by truncated nuclear norm regularization, and a piecewise- smooth prior on spatial dimension can be embedded by a linear total variation-norm regularization. For anomaly tensor, it is unfolded along spectral dimension coupled with spatial group sparse prior that can be represented by l 2,1 -norm regularization.
cl1314/SAED_TGRS
X. Wang, Y. Zhong, C. Cui, L. Zhang and Y. Xu, "Autonomous Endmember Detection via an Abundance Anomaly Guided Saliency Prior for Hyperspectral Imagery," in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 3, pp. 2336-2351, March 2021, doi: 10.1109/TGRS.2020.3001353.
cl1314/SSFSCRD
An novel hyperspectral anomaly detection method.
cl1314/VABS
Hyperspectral Anomaly Detection