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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/chongjiange/care
공식 코드Revitalizing CNN Attentions via Transformers in Self-Supervised Visual Representation Learning
https://github.com/chongqingnosubway/dgr-mil
공식 코드https://github.com/chou141253/FGVC-HERBS
공식 코드Fine-grained Visual Classification with High-temperature Refinement and Background Suppression
https://github.com/chou141253/fgvc-pim
공식 코드A Novel Plug-in Module for Fine-Grained Visual Classification
https://github.com/chrhenning/uncertainty_based_ood
공식 코드On out-of-distribution detection with Bayesian neural networks
https://github.com/chris210634/ice
공식 코드Image-Caption Encoding for Improving Zero-Shot Generalization
https://github.com/chrismats/medical_transformers
공식 코드Pretrained ViTs Yield Versatile Representations For Medical Images
https://github.com/christinaheinze/core
공식 코드https://github.com/christophbrgr/ood_detection_framework
공식 코드Confidence-based Out-of-Distribution Detection: A Comparative Study and Analysis
https://github.com/christophstoeckl/FS-neurons
공식 코드Optimized spiking neurons classify images with high accuracy through temporal coding with two spikes
https://github.com/chrisyxue/RCN_for_Interpretable_few_shot
공식 코드Region Comparison Network for Interpretable Few-shot Image Classification
https://github.com/chuangua/contrastivelossmlml
공식 코드Label Structure Preserving Contrastive Embedding for Multi-Label Learning with Missing Labels
https://github.com/chuiyunjun/projectCSC413
공식 코드Effectiveness of Optimization Algorithms in Deep Image Classification
https://github.com/ciao-seohyeon/l2e
공식 코드https://github.com/cics-nd/pde-surrogate
공식 코드https://github.com/cihangxie/DI-2-FGSM
공식 코드Improving Transferability of Adversarial Examples with Input Diversity
https://github.com/cihangxie/NIPS2017_adv_challenge_defense
공식 코드https://github.com/cindyxinyiwang/DataSelection
공식 코드https://github.com/cinofix/sponge_poisoning_energy_latency_attack
공식 코드https://github.com/cis-ncbj/covid19-stylegan-augmentation
공식 코드Performance of GAN-based augmentation for deep learning COVID-19 image classification
https://github.com/citychan/federated-dpms
공식 코드Federated Learning in Non-IID Settings Aided by Differentially Private Synthetic Data
https://github.com/cityu-aim-group/gfbs
공식 코드Exploring Gradient Flow Based Saliency for DNN Model Compression
https://github.com/cityu-aim-group/jcas
공식 코드Joint Class-Affinity Loss Correction for Robust Medical Image Segmentation with Noisy Labels
https://github.com/ck-amrahd/birds
공식 코드Improving the trustworthiness of image classification models by utilizing bounding-box annotations
https://github.com/ckn3/sa-recon
공식 코드https://github.com/ckyrkou/AIDER
공식 코드https://github.com/ckyrkou/EmergencyNet
공식 코드https://github.com/ckyrkou/step_models
공식 코드Toward Efficient Convolutional Neural Networks With Structured Ternary Patterns
https://github.com/cl-premonition/premonition
공식 코드Premonition: Using Generative Models to Preempt Future Data Changes in Continual Learning
https://github.com/clbonet/Hyperbolic_Sliced-Wasserstein_via_Geodesic_and_Horospherical_Projections
공식 코드Hyperbolic Sliced-Wasserstein via Geodesic and Horospherical Projections
https://github.com/cleanlab/cleanlab
공식 코드Confident Learning: Estimating Uncertainty in Dataset Labels
https://github.com/cleanlab/ood-detection-benchmarks
공식 코드Back to the Basics: Revisiting Out-of-Distribution Detection Baselines
https://github.com/clear-nus/diffpath
공식 코드Out-of-Distribution Detection with a Single Unconditional Diffusion Model
https://github.com/clearproject/clear
공식 코드Conceptual Learning via Embedding Approximations for Reinforcing Interpretability and Transparency
https://github.com/cleopatra-itn/GeoWINE
공식 코드GeoWINE: Geolocation based Wiki, Image,News and Event Retrieval
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.