Image Classification
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Image Classification is a fundamental task in vision recognition that aims to understand and categorize an image as a whole under a specific label. Unlike object detection, which involves classification and location of multiple objects within an image, image classification typically pertains to single-object images. When the classification becomes highly detailed or reaches instance-level, it is often referred to as image retrieval, which also involves finding similar images in a large database.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/HIPS/Spearmint
Practical Bayesian Optimization of Machine Learning Algorithms
https://github.com/HLinShan/vision_networks
https://github.com/HO4X/TSR_JetsonTX2
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
https://github.com/HSISeg/HSISeg
PUNCH: Positive UNlabelled Classification based information retrieval in Hyperspectral images
https://github.com/HSRW-EMRP-WS1920-Drone/object_detection_and_landing
CSPNet: A New Backbone that can Enhance Learning Capability of CNN
https://github.com/Hadisalman/robust-verify-benchmark
Towards Deep Learning Models Resistant to Adversarial Attacks
https://github.com/HaijunMa/GAN
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/HaijunMa/GAN-Getting-started-learning
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/Halesu/4th-ML100Days
https://github.com/HaloTrouvaille/YOLO-Multi-Backbones-Attention
https://github.com/HamadYA/GhostFaceNets
https://github.com/Han-JD/GRU-D
https://github.com/HanxunHuangLemonBear/SCELoss-Reproduce
Symmetric Cross Entropy for Robust Learning with Noisy Labels
https://github.com/HaoJunNM/Unet-PretrainedMobilenetV2encoder-Flaskapp
https://github.com/HaohanWang/ImageNet-Sketch
https://github.com/Haoqing-Wang/CPNWCP
https://github.com/HaoyueBaiZJU/DecAug
https://github.com/HarmanDotpy/Normalizations-in-Deep-Learning
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Harry-Muzart/harry-muzart.github.io
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/HarshaVardhanVanama/Synthetic-Medical-Images
Synthetic Medical Images from Dual Generative Adversarial Networks
https://github.com/Hashir44/muraxray
https://github.com/Hazelsuko07/InstaHide
https://github.com/Hazqeel09/ellzaf_ml
https://github.com/HazyResearch/m2
Monarch Mixer: A Simple Sub-Quadratic GEMM-Based Architecture
https://github.com/He-jerry/DSSNet
https://github.com/He-jerry/U2Net-Tensorflow
U$^2$-Net: Going Deeper with Nested U-Structure for Salient Object Detection
https://github.com/HeapHop30/graph-attention-nets
Geometric deep learning on graphs and manifolds using mixture model CNNs
https://github.com/Helsinki-NLP/OpenNMT-py
https://github.com/HenonBamboo/PSPNet-MindSpore
https://github.com/HenryCWoo/LTLProject
https://github.com/HenryLHH/HVAE-OOD
https://github.com/HeungChangLee/AutoML
https://github.com/HiGal/Domain-Adaptation
Maximum Classifier Discrepancy for Unsupervised Domain Adaptation
https://github.com/HibikiJie/BYOL
Bootstrap your own latent: A new approach to self-supervised Learning
https://github.com/HighCWu/stylegan2-paddle
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.