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 7351–7400 of 10420 papers

TitleStatusHype
Amortized Proximal Optimization—0
Invariance-Guided Feature Evolution for Few-Shot Learning—0
Performing Image Classification for 10 Different Monkey Species using CNN—0
Peri-Net-Pro: The neural processes with quantified uncertainty for crack patterns—0
Deep Learning in the Automotive Industry: Applications and Tools—0
Intuitionistic Fuzzy Cognitive Maps for Interpretable Image Classification—0
Intrusion Detection: Machine Learning Baseline Calculations for Image Classification—0
Deep Learning in Medical Image Classification from MRI-based Brain Tumor Images—0
Introspection for convolutional automatic speech recognition—0
Introduction to Camera Pose Estimation with Deep Learning—0
Personalized Federated Learning with Local Attention—0
Personalized Food Image Classification: Benchmark Datasets and New Baseline—0
Introducing the structural bases of typicality effects in deep learning—0
Personalized Semantics Excitation for Federated Image Classification—0
Person Re-identification: Past, Present and Future—0
pFedSOP : Accelerating Training Of Personalized Federated Learning Using Second-Order Optimization—0
Deep Learning in Image Classification: Evaluating VGG19's Performance on Complex Visual Data—0
Introducing Fuzzy Layers for Deep Learning—0
Robustness via Deep Low-Rank Representations—0
Deep Learning Hyperspectral Image Classification Using Multiple Class-based Denoising Autoencoders, Mixed Pixel Training Augmentation, and Morphological Operations—0
Intriguing Frequency Interpretation of Adversarial Robustness for CNNs and ViTs—0
Intra-Model Collaborative Learning of Neural Networks—0
Deep Learning: Generalization Requires Deep Compositional Feature Space Design—0
Interventional Black-Box Explanations—0
Interpreting Undesirable Pixels for Image Classification on Black-Box Models—0
Deep Learning Generalization, Extrapolation, and Over-parameterization—0
Deep Learning Generalization and the Convex Hull of Training Sets—0
A Modified Perturbed Sampling Method for Local Interpretable Model-agnostic Explanation—0
Adaptive Image Anonymization in the Context of Image Classification with Neural Networks—0
Interpreting the Predictions of Complex ML Models by Layer-wise Relevance Propagation—0
Interpreting Interpretations: Organizing Attribution Methods by Criteria—0
Deep Learning Framework for Multi-class Breast Cancer Histology Image Classification—0
Interpreting Equivariant Representations—0
Interpreting Bias in the Neural Networks: A Peek Into Representational Similarity—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
Interpretable Mammographic Image Classification using Case-Based Reasoning and Deep Learning—0
BAFFLE: TOWARDS RESOLVING FEDERATED LEARNING’S DILEMMA - THWARTING BACKDOOR AND INFERENCE ATTACKS—0
Interpretable Few-Shot Image Classification via Prototypical Concept-Guided Mixture of LoRA Experts—0
Deep Learning for Hyperspectral Image Classification: An Overview—0
Pixel-level Reconstruction and Classification for Noisy Handwritten Bangla Characters—0
Interpretable Failure Detection with Human-Level Concepts—0
Interpretable Deep Models for Cardiac Resynchronisation Therapy Response Prediction—0
Deep Learning For Computer Vision Tasks: A review—0
PK-GCN: Prior Knowledge Assisted Image Classification using Graph Convolution Networks—0
Place recognition: An Overview of Vision Perspective—0
BadScan: An Architectural Backdoor Attack on Visual State Space Models—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