https://github.com/Yunodo/maxup
MaxUp: A Simple Way to Improve Generalization of Neural Network Training
Papers with Code 아카이브
General Classification
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Algorithms trying to solve the general task of classification.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/YuriBogdanov/DeepPacket
Deep Packet: A Novel Approach For Encrypted Traffic Classification Using Deep Learning
https://github.com/YushiChen/Auto-CNN-HSI-Classification
https://github.com/YutingLi0606/SURE
CleanNet: Transfer Learning for Scalable Image Classifier Training with Label Noise
https://github.com/YutongWangUMich/UCI_classification
Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks
https://github.com/YuvalBahat/Confidence_From_Invariance
https://github.com/Yuxiang1995/ICDAR2021_MFD
Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection
https://github.com/YuxiangRen/Heterogeneous-Deep-Graph-Infomax
https://github.com/YyzHarry/imbalanced-semi-self
Unsupervised Representation Learning by Predicting Image Rotations
https://github.com/ZHKKKe/PixelSSL
Semi-supervised semantic segmentation needs strong, varied perturbations
https://github.com/ZJCV/X3D
X3D: Expanding Architectures for Efficient Video Recognition
https://github.com/ZJUHSY/2020-
https://github.com/ZJULearning/graph_level_drug_discovery
https://github.com/ZJUT-ERCISS/zjut_mindvideo/blob/master/msvideo/models/i3d.py
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
https://github.com/ZTao-z/multiflow-resnet-ssd
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/ZZUFaceBookDL/Gated_Transformer_Network
Gated Transformer Networks for Multivariate Time Series Classification
https://github.com/ZZhangyutong/fasttext
https://github.com/ZZy979/CDL-LDA
Cross-Domain Labeled LDA for Cross-Domain Text Classification
https://github.com/ZacharyChenpk/Local_ETHZ
Neural Fine-Grained Entity Type Classification with Hierarchy-Aware Loss
https://github.com/ZacharyGoshen/cifar-10-classifier
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/ZacharyHimmelberger/image-classification-for-technical-indicators
https://github.com/Zafiirah13/ICVaS
https://github.com/Zafiirah13/Imbalance-Learning-for-Variable-Star-Classification-using-Machine-Learning
https://github.com/ZaydH/covariate_shift_risk_estimation
Classification from Positive, Unlabeled and Biased Negative Data
https://github.com/Ze-Yang/Context-Transformer
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/ZeinabRahbar/Implementation-for-the-paper-of-SEMI-SUPERVISED-CLASSIFICATION-WITH-GRAPH-CONVOLUTIONAL-NETWORKS
Semi-Supervised Classification with Graph Convolutional Networks
https://github.com/ZekuiQin/SiamKPN
SiamFC++: Towards Robust and Accurate Visual Tracking with Target Estimation Guidelines
https://github.com/Zelgunn/CustomKerasLayers
Fixup Initialization: Residual Learning Without Normalization
https://github.com/Zeyuan-Wang/AMI-Net
https://github.com/Zhachory1/MusicNST
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Zhang-Jing-Xuan/MaskRCNN
Is Heuristic Sampling Necessary in Training Deep Object Detectors?
https://github.com/Zhanghongbin-github/SegNet-Tutorial
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
https://github.com/ZhenJie-Zhang/darknet_shoe
https://github.com/Zhenye-Na/image-similarity-using-deep-ranking
https://github.com/ZhimingZhou/AM-GAN
Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks
https://github.com/ZhinusMarzi/Adversarial-attack
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.