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 4451–4475 of 10420 papers

TitleStatusHype
How to use model architecture and training environment to estimate the energy consumption of DL trainingCode0
Distilling Self-Supervised Vision Transformers for Weakly-Supervised Few-Shot Classification & Segmentation—0
Learning Curves for Noisy Heterogeneous Feature-Subsampled Ridge EnsemblesCode0
Art Authentication with Vision Transformers—0
Improving the Efficiency of Human-in-the-Loop Systems: Adding Artificial to Human ExpertsCode0
A Novel Site-Agnostic Multimodal Deep Learning Model to Identify Pro-Eating Disorder Content on Social Media—0
The Role of Subgroup Separability in Group-Fair Medical Image ClassificationCode0
Multi-Similarity Contrastive Learning—0
Adversarial Attacks on Image Classification Models: FGSM and Patch Attacks and their Impact—0
Make A Long Image Short: Adaptive Token Length for Vision Transformers—0
Multi-Scale U-Shape MLP for Hyperspectral Image Classification—0
A ChatGPT Aided Explainable Framework for Zero-Shot Medical Image Diagnosis—0
Multi-Scale Prototypical Transformer for Whole Slide Image Classification—0
UX Heuristics and Checklist for Deep Learning powered Mobile Applications with Image Classification—0
A Neural Collapse Perspective on Feature Evolution in Graph Neural NetworksCode0
Continual Learning in Open-vocabulary Classification with Complementary Memory SystemsCode0
Mitigating Bias: Enhancing Image Classification by Improving Model Explanations—0
In-Domain Self-Supervised Learning Improves Remote Sensing Image Scene Classification—0
Structured Network Pruning by Measuring Filter-wise Interactions—0
Review helps learn better: Temporal Supervised Knowledge Distillation—0
Why do CNNs excel at feature extraction? A mathematical explanation—0
Query-Efficient Decision-based Black-Box Patch Attack—0
The Forward-Forward Algorithm as a feature extractor for skin lesion classification: A preliminary study—0
SysNoise: Exploring and Benchmarking Training-Deployment System Inconsistency—0
Single-Stage Heavy-Tailed Food Classification—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
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
6DaViT-HTop 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
10RevCol-HTop 1 Accuracy90—Unverified