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 8951–9000 of 10420 papers

TitleStatusHype
Establishment of Neural Networks Robust to Label Noise—0
Estimating Physical Information Consistency of Channel Data Augmentation for Remote Sensing Images—0
Estimating the Brittleness of AI: Safety Integrity Levels and the Need for Testing Out-Of-Distribution Performance—0
Estimating the Robustness of Classification Models by the Structure of the Learned Feature-Space—0
Estimation with Uncertainty via Conditional Generative Adversarial Networks—0
ESW Edge-Weights : Ensemble Stochastic Watershed Edge-Weights for Hyperspectral Image Classification—0
Evaluating Adversarial Robustness: A Comparison Of FGSM, Carlini-Wagner Attacks, And The Role of Distillation as Defense Mechanism—0
Evaluating Adversarial Robustness on Document Image Classification—0
Evaluating a Synthetic Image Dataset Generated with Stable Diffusion—0
Evaluating Capability of Deep Neural Networks for Image Classification via Information Plane—0
Evaluating CLIP: Towards Characterization of Broader Capabilities and Downstream Implications—0
Evaluating COPY-BLEND Augmentation for Low Level Vision Tasks—0
Evaluating Data Augmentation Techniques for Coffee Leaf Disease Classification—0
Evaluating Deep Convolutional Neural Networks for Material Classification—0
c-Eval: A Unified Metric to Evaluate Feature-based Explanations via Perturbation—0
Evaluating Language-biased image classification based on semantic compositionality—0
Evaluating the Effectiveness of Efficient Neural Architecture Search for Sentence-Pair Tasks—0
Evaluating the Fairness of Neural Collapse in Medical Image Classification—0
Evaluating the performance of the LIME and Grad-CAM explanation methods on a LEGO multi-label image classification task—0
Evaluating the Progress of Deep Learning for Visual Relational Concepts—0
Evaluating the Robustness of Bayesian Neural Networks Against Different Types of Attacks—0
Evaluating The Robustness of Self-Supervised Representations to Background/Foreground Removal—0
Evaluation of Big Data based CNN Models in Classification of Skin Lesions with Melanoma—0
Evaluation of Confidence-based Ensembling in Deep Learning Image Classification—0
Evaluation of Deep Convolutional Nets for Document Image Classification and Retrieval—0
Evaluation of Deep Learning on an Abstract Image Classification Dataset—0
Fidelity of Interpretability Methods and Perturbation Artifacts in Neural Networks—0
Evaluation of Transfer Learning for Classification of: (1) Diabetic Retinopathy by Digital Fundus Photography and (2) Diabetic Macular Edema, Choroidal Neovascularization and Drusen by Optical Coherence Tomography—0
Evaluation, Tuning and Interpretation of Neural Networks for Meteorological Applications—0
Event-Based Control for Online Training of Neural Networks—0
Evidence-empowered Transfer Learning for Alzheimer's Disease—0
Evidential Federated Learning for Skin Lesion Image Classification—0
EVM-Fusion: An Explainable Vision Mamba Architecture with Neural Algorithmic Fusion—0
Evolutionary Cell Aided Design for Neural Network Architectures—0
Evolutionary Multi-objective Optimisation in Neurotrajectory Prediction—0
Evolutionary Neural Architecture Search for Image Restoration—0
Evolutionary-Neural Hybrid Agents for Architecture Search—0
Evolutionary Synthesis of Deep Neural Networks via Synaptic Cluster-driven Genetic Encoding—0
Evolution-aware VAriance (EVA) Coreset Selection for Medical Image Classification—0
Evolution of Activation Functions for Deep Learning-Based Image Classification—0
Evolution of active categorical image classification via saccadic eye movement—0
Evolved Explainable Classifications for Lymph Node Metastases—0
Evolved Part Masking for Self-Supervised Learning—0
Evolving Character-Level DenseNet Architectures using Genetic Programming—0
Evolving Deep Convolutional Neural Networks by Variable-length Particle Swarm Optimization for Image Classification—0
Evolving Efficient CNN Based Model for Image Classification—0
Evolving parametrized Loss for Image Classification Learning on Small Datasets—0
Evo-NAS: Evolutionary-Neural Hybrid Agent for Architecture Search—0
EWasteNet: A Two-Stream Data Efficient Image Transformer Approach for E-Waste Classification—0
Examining convolutional feature extraction using Maximum Entropy (ME) and Signal-to-Noise Ratio (SNR) 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