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/IS2AI/Chest-X-ray-module
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/ISS-Kerui/BIRA-NET-BILINEAR-ATTENTION-NET-FOR-DIABETIC-RETINOPATHY-GRADING
BiRA-Net: Bilinear Attention Net for Diabetic Retinopathy Grading
https://github.com/Ian-Liao/SegCaps
https://github.com/IcarusWizard/MAE
https://github.com/IgorSusmelj/barlowtwins
Barlow Twins: Self-Supervised Learning via Redundancy Reduction
https://github.com/IgorSusmelj/simsiam-cifar10
https://github.com/IlyaDobrynin/GridMixup
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
https://github.com/IlyaOvodov/AngelinaReader
https://github.com/Imageomics/Prompt_CAM
Prompt-CAM: A Simpler Interpretable Transformer for Fine-Grained Analysis
https://github.com/IndicoDataSolutions/finetune
https://github.com/IntelLabs/bayesian-torch
Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes
https://github.com/Ipsedo/MARLClassification
https://github.com/IsaacPatole/DCGAN-and-CGAN
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
https://github.com/IsaacRodgz/ConcatBERT
https://github.com/IsaacRodgz/GMU-Baseline
https://github.com/IsaacRodgz/mmbt_experiments
https://github.com/IsaacRodgz/multimodal-transformers-movies
https://github.com/IsmaelCesar/darts
https://github.com/IssamLaradji/sps
Gradient Centralization: A New Optimization Technique for Deep Neural Networks
https://github.com/IvanPy96/Clothes-images-classification
Aggregated Residual Transformations for Deep Neural Networks
https://github.com/IyatomiLab/CE-CLCNN
https://github.com/Izecson/saml-nmt
https://github.com/Izecson/sockeye-1.16.6
https://github.com/J911/WRN-pytorch
https://github.com/JCamERG/YOLOPersonal
CSPNet: A New Backbone that can Enhance Learning Capability of CNN
https://github.com/JContro/pytorch_projects
https://github.com/JDAI-CV/CoTNet
https://github.com/JDAI-CV/CoTNet-ObjectDetection-InstanceSegmentation
https://github.com/JDAI-CV/DCL
Look-into-Object: Self-supervised Structure Modeling for Object Recognition
https://github.com/JDAI-CV/dabnn
https://github.com/JEKimLab/ICLR2025_SpuriousDataPruning
Just Train Twice: Improving Group Robustness without Training Group Information
https://github.com/JEONGHA-SHIN/YOGO_Server_v2
CSPNet: A New Backbone that can Enhance Learning Capability of CNN
https://github.com/JH-LEE-KR/l2p-pytorch
https://github.com/JHKim-snu/GVCCI
https://github.com/JHKim-snu/PGA
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.