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 3101–3125 of 10420 papers

TitleStatusHype
ACLS: Adaptive and Conditional Label Smoothing for Network Calibration—0
Exemplar SVMs as Visual Feature Encoders—0
Discriminative and Geometry Aware Unsupervised Domain Adaptation—0
Distilling High Diagnostic Value Patches for Whole Slide Image Classification Using Attention Mechanism—0
An End-to-End Breast Tumour Classification Model Using Context-Based Patch Modelling- A BiLSTM Approach for Image Classification—0
Distilling Knowledge into Quantum Vision Transformers for Biomedical Image Classification—0
An Empirical Investigation into Benchmarking Model Multiplicity for Trustworthy Machine Learning: A Case Study on Image Classification—0
Exemplar Based Deep Discriminative and Shareable Feature Learning for Scene Image Classification—0
Self-Attention Capsule Networks for Object Classification—0
Exemplar-free Online Continual Learning—0
ExMobileViT: Lightweight Classifier Extension for Mobile Vision Transformer—0
Experimental Observations of the Topology of Convolutional Neural Network Activations—0
Discriminability-enforcing loss to improve representation learning—0
An Empirical Evaluation of Sketched SVD and its Application to Leverage Score Ordering—0
Discrete Wavelet Transform-Based Capsule Network for Hyperspectral Image Classification—0
Boosting Convolutional Features for Robust Object Proposals—0
Examining the Proximity of Adversarial Examples to Class Manifolds in Deep Networks—0
GTAdam: Gradient Tracking with Adaptive Momentum for Distributed Online Optimization—0
Discrete Simulation Optimization for Tuning Machine Learning Method Hyperparameters—0
An Embedding-Dynamic Approach to Self-supervised Learning—0
Distributed Training of Deep Neural Networks with Theoretical Analysis: Under SSP Setting—0
Distributed Transfer Learning with 4th Gen Intel Xeon Processors—0
Distribution Adaptive INT8 Quantization for Training CNNs—0
Task-Robust Model-Agnostic Meta-Learning—0
Addressing out-of-distribution label noise in webly-labelled data—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