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 3351–3375 of 10420 papers

TitleStatusHype
Rescaling Large Datasets Based on Validation Outcomes of a Pre-trained NetworkCode0
Scarecrow monitoring system:employing mobilenet ssd for enhanced animal supervision—0
Formal Verification of Deep Neural Networks for Object Detection—0
Semantic Compositions Enhance Vision-Language Contrastive Learning—0
Gradient-based Class Weighting for Unsupervised Domain Adaptation in Dense Prediction Visual Tasks—0
Image Classification for Snow Detection to Improve Pedestrian Safety—0
ModelVerification.jl: a Comprehensive Toolbox for Formally Verifying Deep Neural Networks—0
RepAct: The Re-parameterizable Adaptive Activation FunctionCode0
Extract More from Less: Efficient Fine-Grained Visual Recognition in Low-Data RegimesCode0
Assistive Image Annotation Systems with Deep Learning and Natural Language Capabilities: A Review—0
Learning Visual Conditioning Tokens to Correct Domain Shift for Fully Test-time Adaptation—0
Adaptive Stochastic Weight AveragingCode0
Instance Temperature Knowledge DistillationCode0
Optimization of Autonomous Driving Image Detection Based on RFAConv and Triplet Attention—0
TSynD: Targeted Synthetic Data Generation for Enhanced Medical Image Classification—0
Structured Unrestricted-Rank Matrices for Parameter Efficient Fine-tuningCode0
Robustly Optimized Deep Feature Decoupling Network for Fatty Liver Diseases DetectionCode0
Dynamic Scheduling for Vehicle-to-Vehicle Communications Enhanced Federated Learning—0
Benchmarking Deep Learning Models on NVIDIA Jetson Nano for Real-Time Systems: An Empirical InvestigationCode0
BayTTA: Uncertainty-aware medical image classification with optimized test-time augmentation using Bayesian model averagingCode0
Combining Supervised Learning and Reinforcement Learning for Multi-Label Classification Tasks with Partial Labels—0
Speeding Up Image Classifiers with Little Companions—0
Diff3Dformer: Leveraging Slice Sequence Diffusion for Enhanced 3D CT Classification with Transformer Networks—0
Improving robustness to corruptions with multiplicative weight perturbationsCode0
Improving Quaternion Neural Networks with Quaternionic Activation Functions—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