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 5926–5950 of 10420 papers

TitleStatusHype
Diagnosis of Skin Cancer Using VGG16 and VGG19 Based Transfer Learning Models—0
Text Descriptions are Compressive and Invariant Representations for Visual Learning—0
Leveraging Perceptual Scores for Dataset Pruning in Computer Vision Tasks—0
Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Data—0
Leveraging Spatial and Semantic Feature Extraction for Skin Cancer Diagnosis with Capsule Networks and Graph Neural Networks—0
Leveraging Superfluous Information in Contrastive Representation Learning—0
Leveraging Systematic Knowledge of 2D Transformations—0
MedFocusCLIP : Improving few shot classification in medical datasets using pixel wise attention—0
Break a Lag: Triple Exponential Moving Average for Enhanced Optimization—0
MDL-NAS: A Joint Multi-Domain Learning Framework for Vision Transformer—0
Attack Agnostic Statistical Method for Adversarial Detection—0
Grassmann Pooling as Compact Homogeneous Bilinear Pooling for Fine-Grained Visual Classification—0
LEVIS: Large Exact Verifiable Input Spaces for Neural Networks—0
GRASP: A Rehearsal Policy for Efficient Online Continual Learning—0
Coupled End-to-End Transfer Learning With Generalized Fisher Information—0
Measuring directional bias amplification in image captions using predictability—0
AT-SNN: Adaptive Tokens for Vision Transformer on Spiking Neural Network—0
GraphViz2Vec: A Structure-aware Feature Generation Model to Improve Classification in GNNs—0
DIET-SNN: Direct Input Encoding With Leakage and Threshold Optimization in Deep Spiking Neural Networks—0
Diff3Dformer: Leveraging Slice Sequence Diffusion for Enhanced 3D CT Classification with Transformer Networks—0
Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups—0
A Hybrid Architecture for On-Device Compressive Machine Learning—0
DiffCLIP: Leveraging Stable Diffusion for Language Grounded 3D Classification—0
Graph Structural Aggregation for Explainable Learning—0
Graphs for deep learning representations—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