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

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Showing 4401–4450 of 10420 papers

TitleStatusHype
A Modified Perturbed Sampling Method for Local Interpretable Model-agnostic Explanation—0
If a Human Can See It, So Should Your System: Reliability Requirements for Machine Vision Components—0
IGroupSS-Mamba: Interval Group Spatial-Spectral Mamba for Hyperspectral Image Classification—0
¶ILCRO: Making Importance Landscapes Flat Again—0
Deep Learning Framework for Multi-class Breast Cancer Histology Image Classification—0
Deep Learning for Multi-Level Detection and Localization of Myocardial Scars Based on Regional Strain Validated on Virtual Patients—0
Deep Learning for Logo Recognition—0
Deep learning for lithological classification of carbonate rock micro-CT images—0
BaFTA: Backprop-Free Test-Time Adaptation For Zero-Shot Vision-Language Models—0
Explanation and Use of Uncertainty Quantified by Bayesian Neural Network Classifiers for Breast Histopathology Images—0
A Model-Agnostic SAT-based Approach for Symbolic Explanation Enumeration—0
BAFFLE: TOWARDS RESOLVING FEDERATED LEARNING’S DILEMMA - THWARTING BACKDOOR AND INFERENCE ATTACKS—0
DomainSiam: Domain-Aware Siamese Network for Visual Object Tracking—0
Deep Learning for Hyperspectral Image Classification: An Overview—0
Deep Learning For Computer Vision Tasks: A review—0
BadScan: An Architectural Backdoor Attack on Visual State Space Models—0
Identifying regions of interest in whole slide images of renal cell carcinoma—0
Identifying Spurious Correlations and Correcting them with an Explanation-based Learning—0
Deep Learning for Climate Action: Computer Vision Analysis of Visual Narratives on X—0
Deep learning for classification of noisy QR codes—0
BadNL: Backdoor Attacks against NLP Models with Semantic-preserving Improvements—0
Deep Learning for Apple Diseases: Classification and Identification—0
Identifying Land Patterns from Satellite Imagery in Amazon Rainforest using Deep Learning—0
Identifying Misinformation from Website Screenshots—0
Deep Learning for Active Region Classification: A Systematic Study from Convolutional Neural Networks to Vision Transformers—0
Identification of Cervical Pathology using Adversarial Neural Networks—0
Identification of Seed Cells in Multispectral Images for GrowCut Segmentation—0
Improved and Explainable Cervical Cancer Classification using Ensemble Pooling of Block Fused Descriptors—0
Deep Learning Classification With Noisy Labels—0
Adaptive Fine-Grained Predicates Learning for Scene Graph Generation—0
Identify Apple Leaf Diseases Using Deep Learning Algorithm—0
Identifying Mislabeled Images in Supervised Learning Utilizing Autoencoder—0
Illuminated Decision Trees with Lucid—0
Deep Learning Benchmarks and Datasets for Social Media Image Classification for Disaster Response—0
Deep learning based prediction of Alzheimer's disease from magnetic resonance images—0
AMLA: an AutoML frAmework for Neural Network Design—0
Deep Learning based Multi-Label Image Classification of Protest Activities—0
Deep Learning based HEp-2 Image Classification: A Comprehensive Review—0
Backpropagation-free Training of Deep Physical Neural Networks—0
I-CNet: Leveraging Involution and Convolution for Image Classification—0
Deep Learning based CNN Model for Classification and Detection of Individuals Wearing Face Mask—0
Deep Learning Based Classification System For Recognizing Local Spinach—0
Amicable Aid: Perturbing Images to Improve Classification Performance—0
ParasNet: Fast Parasites Detection with Neural Networks—0
Backdoor in Seconds: Unlocking Vulnerabilities in Large Pre-trained Models via Model Editing—0
MCU: Improving Machine Unlearning through Mode Connectivity—0
iConFormer: Dynamic Parameter-Efficient Tuning with Input-Conditioned Adaptation—0
Backdoor Embedding in Convolutional Neural Network Models via Invisible Perturbation—0
Deep Learning-based automated classification of Chinese Speech Sound Disorders—0
AMF: Adaptable Weighting Fusion with Multiple Fine-tuning for Image Classification—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