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 2451–2475 of 10420 papers

TitleStatusHype
Human-aligned Deep Learning: Explainability, Causality, and Biological Inspiration—0
Expert Kernel Generation Network Driven by Contextual Mapping for Hyperspectral Image ClassificationCode0
Quantum Computing Supported Adversarial Attack-Resilient Autonomous Vehicle Perception Module for Traffic Sign ClassificationCode0
Dynamic Memory-enhanced Transformer for Hyperspectral Image Classification—0
Weakly Semi-supervised Whole Slide Image Classification by Two-level Cross Consistency Supervision—0
FLIP Reasoning ChallengeCode0
Exploring Video-Based Driver Activity Recognition under Noisy LabelsCode0
GLUSE: Enhanced Channel-Wise Adaptive Gated Linear Units SE for Onboard Satellite Earth Observation Image ClassificationCode0
Deep Learning Approaches for Medical Imaging Under Varying Degrees of Label Availability: A Comprehensive Survey—0
3D Wavelet Convolutions with Extended Receptive Fields for Hyperspectral Image ClassificationCode0
Diversity-Driven Learning: Tackling Spurious Correlations and Data Heterogeneity in Federated Models—0
Embedding Radiomics into Vision Transformers for Multimodal Medical Image Classification—0
Sparse Deformable Mamba for Hyperspectral Image Classification—0
An Efficient Quantum Classifier Based on Hamiltonian RepresentationsCode0
MGS: Markov Greedy Sums for Accurate Low-Bitwidth Floating-Point Accumulation—0
Comparative Analysis of Different Methods for Classifying Polychromatic Sketches—0
Hypergraph Vision Transformers: Images are More than Nodes, More than Edges—0
FocalLens: Instruction Tuning Enables Zero-Shot Conditional Image Representations—0
A Hybrid Fully Convolutional CNN-Transformer Model for Inherently Interpretable Medical Image Classification—0
MultiCore+TPU Accelerated Multi-Modal TinyML for Livestock Behaviour Recognition—0
Identifying regions of interest in whole slide images of renal cell carcinoma—0
Memory-Modular Classification: Learning to Generalize with Memory ReplacementCode0
Gaze-Guided Learning: Avoiding Shortcut Bias in Visual ClassificationCode0
Federated Unlearning Made Practical: Seamless Integration via Negated Pseudo-GradientsCode0
Secure Diagnostics: Adversarial Robustness Meets Clinical Interpretability—0
Show:102550
← PrevPage 99 of 417Next →
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