SOTAVerified

Image Classification

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.

Source: Metamorphic Testing for Object Detection Systems

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3726–3750 of 10420 papers

TitleStatusHype
Temporal Decisions: Leveraging Temporal Correlation for Efficient Decisions in Early Exit Neural Networks—0
12 mJ per Class On-Device Online Few-Shot Class-Incremental LearningCode0
Premonition: Using Generative Models to Preempt Future Data Changes in Continual LearningCode0
How does promoting the minority fraction affect generalization? A theoretical study of the one-hidden-layer neural network on group imbalance—0
Backdoor Attack with Mode Mixture Latent Modification—0
In-context learning enables multimodal large language models to classify cancer pathology images—0
A Bayesian Approach to OOD Robustness in Image ClassificationCode0
Shortcut Learning in Medical Image SegmentationCode0
A Converting Autoencoder Toward Low-latency and Energy-efficient DNN Inference at the Edge—0
Dynamic Perturbation-Adaptive Adversarial Training on Medical Image Classification—0
Leveraging Internal Representations of Model for Magnetic Image Classification—0
Deep Learning Recognition for Arabic Alphabet Sign Language RGB Dataset—0
LeOCLR: Leveraging Original Images for Contrastive Learning of Visual Representations—0
Active Generation for Image ClassificationCode0
Debiased Noise Editing on Foundation Models for Fair Medical Image ClassificationCode0
BSDA: Bayesian Random Semantic Data Augmentation for Medical Image ClassificationCode0
Probing Image Compression For Class-Incremental Learning—0
Are Classification Robustness and Explanation Robustness Really Strongly Correlated? An Analysis Through Input Loss Landscape—0
Dynamic Policy-Driven Adaptive Multi-Instance Learning for Whole Slide Image Classification—0
Multiple Instance Learning with random sampling for Whole Slide Image Classification—0
Generalized Correspondence Matching via Flexible Hierarchical Refinement and Patch Descriptor Distillation—0
Feature CAM: Interpretable AI in Image Classification—0
Tune without Validation: Searching for Learning Rate and Weight Decay on Training Sets—0
ComFe: Interpretable Image Classifiers With Foundation Models, Transformers and Component FeaturesCode0
Fooling Neural Networks for Motion Forecasting via Adversarial Attacks—0
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All datasetsImageNetCIFAR-10CIFAR-100STL-10ObjectNetMNISTSVHNiNaturalist 2018ImageNet ReaLFlowers-102Clothing1Mmini WebVision 1.0

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91—Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98—Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94—Unverified
4DaViT-GTop 1 Accuracy90.4—Unverified
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
7SwinV2-GTop 1 Accuracy90.17—Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1—Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05—Unverified
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified