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 6451–6475 of 10420 papers

TitleStatusHype
An Attention Module for Convolutional Neural Networks—0
Confidence Adaptive Regularization for Deep Learning with Noisy Labels—0
Federated Multi-Target Domain Adaptation—0
OncoPetNet: A Deep Learning based AI system for mitotic figure counting on H&E stained whole slide digital images in a large veterinary diagnostic lab setting—0
Edge AI without Compromise: Efficient, Versatile and Accurate Neurocomputing in Resistive Random-Access Memory—0
Scaling Laws for Deep Learning—0
KCNet: An Insect-Inspired Single-Hidden-Layer Neural Network with Randomized Binary Weights for Prediction and Classification TasksCode0
Investigating a Baseline Of Self Supervised Learning Towards Reducing Labeling Costs For Image Classification—0
Towards Efficient and Data Agnostic Image Classification Training Pipeline for Embedded Systems—0
FedChain: Chained Algorithms for Near-Optimal Communication Cost in Federated Learning—0
Online Continual Learning For Visual Food Classification—0
Improving the trustworthiness of image classification models by utilizing bounding-box annotationsCode0
SCIDA: Self-Correction Integrated Domain Adaptation from Single- to Multi-label Aerial ImagesCode0
A Sparse Coding Interpretation of Neural Networks and Theoretical Implications—0
Pruning vs XNOR-Net: A Comprehensive Study of Deep Learning for Audio Classification on Edge-devicesCode0
Logit Attenuating Weight Normalization—0
DiagViB-6: A Diagnostic Benchmark Suite for Vision Models in the Presence of Shortcut and Generalization OpportunitiesCode0
Billion-Scale Pretraining with Vision Transformers for Multi-Task Visual Representations—0
Learning from Matured Dumb Teacher for Fine Generalization—0
Reinforcement Learning Approach to Active Learning for Image Classification—0
m-RevNet: Deep Reversible Neural Networks with Momentum—0
Is Differentiable Architecture Search truly a One-Shot Method?—0
Simple black-box universal adversarial attacks on medical image classification based on deep neural networks—0
Cervical Optical Coherence Tomography Image Classification Based on Contrastive Self-Supervised Texture LearningCode0
Statistical Dependency Guided Contrastive Learning for Multiple Labeling in Prenatal Ultrasound—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
10RevCol-HTop 1 Accuracy90—Unverified