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 3801–3825 of 10420 papers

TitleStatusHype
Distilled Gradual Pruning with Pruned Fine-tuningCode0
What to Do When Your Discrete Optimization Is the Size of a Neural Network?Code0
ViGEO: an Assessment of Vision GNNs in Earth ObservationCode0
Balancing the Causal Effects in Class-Incremental Learning—0
Investigation of Federated Learning Algorithms for Retinal Optical Coherence Tomography Image Classification with Statistical HeterogeneityCode0
Mind the Modality Gap: Towards a Remote Sensing Vision-Language Model via Cross-modal Alignment—0
Hybrid CNN Bi-LSTM neural network for Hyperspectral image classification—0
Only My Model On My Data: A Privacy Preserving Approach Protecting one Model and Deceiving Unauthorized Black-Box Models—0
Reducing Texture Bias of Deep Neural Networks via Edge Enhancing DiffusionCode0
I can't see it but I can Fine-tune it: On Encrypted Fine-tuning of Transformers using Fully Homomorphic Encryption—0
Comparing supervised learning dynamics: Deep neural networks match human data efficiency but show a generalisation lagCode0
Experts Don't Cheat: Learning What You Don't Know By Predicting Pairs—0
APALU: A Trainable, Adaptive Activation Function for Deep Learning Networks—0
Comparative Analysis of ImageNet Pre-Trained Deep Learning Models and DINOv2 in Medical Imaging ClassificationCode0
Accuracy of TextFooler black box adversarial attacks on 01 loss sign activation neural network ensembleCode0
Contrastive Learning for Regression on Hyperspectral Data—0
A Random Ensemble of Encrypted Vision Transformers for Adversarially Robust Defense—0
A novel spatial-frequency domain network for zero-shot incremental learning—0
Latent Enhancing AutoEncoder for Occluded Image Classification—0
For Better or For Worse? Learning Minimum Variance Features With Label Augmentation—0
Anomaly Unveiled: Securing Image Classification against Adversarial Patch Attacks—0
Feature Density Estimation for Out-of-Distribution Detection via Normalizing Flows—0
SAE: Single Architecture Ensemble Neural Networks—0
The SkipSponge Attack: Sponge Weight Poisoning of Deep Neural Networks—0
Adaptive Activation Functions for Predictive Modeling with Sparse Experimental DataCode0
Show:102550
← PrevPage 153 of 417Next →
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