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 3401–3450 of 10419 papers

TitleStatusHype
Unifying Synergies between Self-supervised Learning and Dynamic ComputationCode0
MultiNet with Transformers: A Model for Cancer Diagnosis Using Images—0
Counterfactual Explanation and Instance-Generation using Cycle-Consistent Generative Adversarial NetworksCode0
Sanity checks and improvements for patch visualisation in prototype-based image classification—0
AI of Brain and Cognitive Sciences: From the Perspective of First Principles—0
Diagnose Like a Pathologist: Transformer-Enabled Hierarchical Attention-Guided Multiple Instance Learning for Whole Slide Image ClassificationCode1
Scaling Deep Networks with the Mesh Adaptive Direct Search algorithm—0
An Energy-Efficient Reconfigurable Autoencoder Implementation on FPGA—0
A^2-UAV: Application-Aware Content and Network Optimization of Edge-Assisted UAV Systems—0
Img2Tab: Automatic Class Relevant Concept Discovery from StyleGAN Features for Explainable Image Classification—0
Data-aware customization of activation functions reduces neural network error—0
Modeling Uncertain Feature Representation for Domain GeneralizationCode1
First Three Years of the International Verification of Neural Networks Competition (VNN-COMP)—0
Gated Self-supervised Learning For Improving Supervised Learning—0
CLIP the Gap: A Single Domain Generalization Approach for Object DetectionCode1
A Scalable Technique for Weak-Supervised Learning with Domain Constraints—0
Color-NeuraCrypt: Privacy-Preserving Color-Image Classification Using Extended Random Neural Networks—0
Online Class-Incremental Learning For Real-World Food Image ClassificationCode0
1st Place Solution for ECCV 2022 OOD-CV Challenge Image Classification TrackCode0
A Stochastic Proximal Polyak Step SizeCode0
Enhancing ResNet Image Classification Performance by using Parameterized Hypercomplex Multiplication—0
Deep Axial Hypercomplex Networks—0
Multi-label Image Classification using Adaptive Graph Convolutional Networks: from a Single Domain to Multiple Domains—0
Deep Residual Axial Networks—0
Objective Evaluation-based High-efficiency Learning Framework for Hyperspectral Image Classification—0
A Privacy Preserving Method with a Random Orthogonal Matrix for ConvMixer Models—0
Dynamic Grained Encoder for Vision TransformersCode1
Deep Learning based Multi-Label Image Classification of Protest Activities—0
Semi-Supervised Learning with Pseudo-Negative Labels for Image ClassificationCode0
Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked ModelingCode3
Learning Support and Trivial Prototypes for Interpretable Image ClassificationCode1
Image Data Augmentation Approaches: A Comprehensive Survey and Future directionsCode0
Improving Human-AI Collaboration With Descriptions of AI Behavior—0
SEQUENT: Towards Traceable Quantum Machine Learning using Sequential Quantum Enhanced TrainingCode0
Artificial intelligence based glaucoma and diabetic retinopathy detection using MATLAB — retrained AlexNet convolutional neural networkCode0
Skip-Attention: Improving Vision Transformers by Paying Less Attention—0
Convolutional XGBoost (C-XGBOOST) Model for Brain Tumor Detection—0
Semi-MAE: Masked Autoencoders for Semi-supervised Vision Transformers—0
On Fairness of Medical Image Classification with Multiple Sensitive Attributes via Learning Orthogonal RepresentationsCode0
MoBYv2AL: Self-supervised Active Learning for Image ClassificationCode1
TinyMIM: An Empirical Study of Distilling MIM Pre-trained ModelsCode1
Explainability and Robustness of Deep Visual Classification Models—0
A New Perspective to Boost Vision Transformer for Medical Image Classification—0
Acne Severity Grading on Face Images via Extraction and Guidance of Prior KnowledgeCode0
Knockoffs-SPR: Clean Sample Selection in Learning with Noisy LabelsCode1
Accelerate adversarial training with loss guided propagation for robust image classificationCode0
Scene-Aware Label Graph Learning for Multi-Label Image Classification—0
LexLIP: Lexicon-Bottlenecked Language-Image Pre-Training for Large-Scale Image-Text Sparse RetrievalCode1
Class-Aware Patch Embedding Adaptation for Few-Shot Image ClassificationCode1
Growing a Brain with Sparsity-Inducing Generation for Continual LearningCode0
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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