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 5501–5525 of 10420 papers

TitleStatusHype
Learning with Limited Samples -- Meta-Learning and Applications to Communication Systems—0
Knowledge distillation using unlabeled mismatched images—0
HEp-2 Cell Image Classification with Deep Convolutional Neural Networks—0
Accelerating Cardiac MRI Reconstruction with CMRatt: An Attention-Driven Approach—0
Learning to Rank for Active Learning: A Listwise Approach—0
Knowledge-Free Black-Box Watermark and Ownership Proof for Image Classification Neural Networks—0
EA-KD: Entropy-based Adaptive Knowledge Distillation—0
Categorical Knowledge Fused Recognition: Fusing Hierarchical Knowledge with Image Classification through Aligning and Deep Metric Learning—0
Knowledge Graph Embeddings for Multi-Lingual Structured Representations of Radiology Reports—0
HDF: Hybrid Deep Features for Scene Image Representation—0
HD-CNN: Hierarchical Deep Convolutional Neural Networks for Large Scale Visual Recognition—0
Have Large Vision-Language Models Mastered Art History?—0
Bayesian Layer Graph Convolutioanl Network for Hyperspetral Image Classification—0
Adaptive Periodic Averaging: A Practical Approach to Reducing Communication in Distributed Learning—0
AI-Compass: A Comprehensive and Effective Multi-module Testing Tool for AI Systems—0
KO: Kinetics-inspired Neural Optimizer with PDE Simulation Approaches—0
Learning to Sample: an Active Learning Framework—0
Deep reinforced active learning for multi-class image classification—0
Cross-Domain Evaluation of Few-Shot Classification Models: Natural Images vs. Histopathological Images—0
Kolmogorov-Arnold networks for metal surface defect classification—0
Attention Feature Fusion Network via Knowledge Propagation for Automated Respiratory Sound Classification—0
Deep reinforcement learning-based image classification achieves perfect testing set accuracy for MRI brain tumors with a training set of only 30 images—0
Hashing on Nonlinear Manifolds—0
Deep Reinforcement Learning for Task Offloading in UAV-Aided Smart Farm Networks—0
Attention-free Spikformer: Mixing Spike Sequences with Simple Linear Transforms—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