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 3076–3100 of 10420 papers

TitleStatusHype
ViTGuard: Attention-aware Detection against Adversarial Examples for Vision Transformer—0
Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Tensorflow Pretrained Models—0
Data Pruning via Separability, Integrity, and Model Uncertainty-Aware Importance Sampling—0
LARE: Latent Augmentation using Regional Embedding with Vision-Language Model—0
Impact of ML Optimization Tactics on Greener Pre-Trained ML Models—0
Improved Image Classification with Manifold Neural Networks—0
StableMamba: Distillation-free Scaling of Large SSMs for Images and Videos—0
Few-Shot Learning Approach on Tuberculosis Classification Based on Chest X-Ray Images—0
Unraveling the Hessian: A Key to Smooth Convergence in Loss Function LandscapesCode0
Agglomerative Token Clustering—0
Hyperspectral Image Classification Based on Faster Residual Multi-branch Spiking Neural Network—0
Anti-ESIA: Analyzing and Mitigating Impacts of Electromagnetic Signal Injection Attacks—0
Multi-Cohort Framework with Cohort-Aware Attention and Adversarial Mutual-Information Minimization for Whole Slide Image Classification—0
Are Deep Learning Models Robust to Partial Object Occlusion in Visual Recognition Tasks?—0
Frequency-Guided Masking for Enhanced Vision Self-Supervised LearningCode0
InfoDisent: Explainability of Image Classification Models by Information Disentanglement—0
Enhancing Image Classification in Small and Unbalanced Datasets through Synthetic Data Augmentation—0
Leveraging Foundation Models for Efficient Federated Learning in Resource-restricted Edge Networks—0
Byzantine-Robust and Communication-Efficient Distributed Learning via Compressed Momentum Filtering—0
Pushing Joint Image Denoising and Classification to the Edge—0
Classifying Images with CoLaNET Spiking Neural Network -- the MNIST Example—0
DFDG: Data-Free Dual-Generator Adversarial Distillation for One-Shot Federated Learning—0
Efficient Privacy-Preserving KAN Inference Using Homomorphic Encryption—0
Microscopic-Mamba: Revealing the Secrets of Microscopic Images with Just 4M ParametersCode0
A Contrastive Symmetric Forward-Forward Algorithm (SFFA) for Continual Learning Tasks—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