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 551–600 of 10419 papers

TitleStatusHype
Multi-modal Vision Pre-training for Medical Image Analysis—0
DefMamba: Deformable Visual State Space Model—0
Star with Bilinear Mapping—0
MExD: An Expert-Infused Diffusion Model for Whole-Slide Image Classification—0
A Novel Approach using CapsNet and Deep Belief Network for Detection and Identification of Oral Leukopenia—0
Ensuring superior learning outcomes and data security for authorized learner—0
ACIL: Active Class Incremental Learning for Image Classification—0
Uncertainty-Aware Out-of-Distribution Detection with Gaussian Processes—0
FPGA-based Acceleration of Neural Network for Image Classification using Vitis AI—0
Deep Learning in Image Classification: Evaluating VGG19's Performance on Complex Visual Data—0
Hilbert Curve Based Molecular Sequence Analysis—0
A Robust Adversarial Ensemble with Causal (Feature Interaction) Interpretations for Image Classification—0
Few-shot Algorithm Assurance—0
Enhancing Transfer Learning for Medical Image Classification with SMOTE: A Comparative Study—0
Cross-Modal Mapping: Mitigating the Modality Gap for Few-Shot Image Classification—0
On dataset transferability in medical image classificationCode0
Image Classification with Deep Reinforcement Active Learning—0
Multi-label Classification using Deep Multi-order Context-aware Kernel Networks—0
Enhancing Fine-grained Image Classification through Attentive Batch Training—0
Data-Free Group-Wise Fully Quantized Winograd Convolution via Learnable Scales—0
Asymmetrical Reciprocity-based Federated Learning for Resolving Disparities in Medical DiagnosisCode0
An In-Depth Analysis of Adversarial Discriminative Domain Adaptation for Digit ClassificationCode0
Residual Feature-Reutilization Inception Network for Image Classification—0
Assessing Pre-trained Models for Transfer Learning through Distribution of Spectral Components—0
Adversarial Training for Graph Neural Networks via Graph Subspace Energy Optimization—0
Provable Uncertainty Decomposition via Higher-Order Calibration—0
Torque-Aware Momentum—0
VisionGRU: A Linear-Complexity RNN Model for Efficient Image AnalysisCode1
Beyond Gradient Averaging in Parallel Optimization: Improved Robustness through Gradient Agreement FilteringCode1
COBRA: COmBinatorial Retrieval Augmentation for Few-Shot Adaptation—0
DiffFormer: a Differential Spatial-Spectral Transformer for Hyperspectral Image ClassificationCode0
Predicting the Reliability of an Image Classifier under Image Distortion—0
Revisiting MLLMs: An In-Depth Analysis of Image Classification Abilities—0
Forget Vectors at Play: Universal Input Perturbations Driving Machine Unlearning in Image ClassificationCode0
UNEM: UNrolled Generalized EM for Transductive Few-Shot LearningCode0
PB-UAP: Hybrid Universal Adversarial Attack For Image Segmentation—0
Adversarial Attack Against Images Classification based on Generative Adversarial Networks—0
Sensitive Image Classification by Vision Transformers—0
V"Mean"ba: Visual State Space Models only need 1 hidden dimension—0
LEARN: A Unified Framework for Multi-Task Domain Adapt Few-Shot LearningCode0
FairREAD: Re-fusing Demographic Attributes after Disentanglement for Fair Medical Image Classification—0
Towards Interpretable Radiology Report Generation via Concept Bottlenecks using a Multi-Agentic RAGCode1
Continual Learning Using a Kernel-Based Method Over Foundation ModelsCode1
Mamba2D: A Natively Multi-Dimensional State-Space Model for Vision TasksCode1
Till the Layers Collapse: Compressing a Deep Neural Network through the Lenses of Batch Normalization LayersCode0
PSSCL: A progressive sample selection framework with contrastive loss designed for noisy labelsCode0
Modelling Multi-modal Cross-interaction for ML-FSIC Based on Local Feature Selection—0
Zero-Shot Prompting and Few-Shot Fine-Tuning: Revisiting Document Image Classification Using Large Language Models—0
MBInception: A new Multi-Block Inception Model for Enhancing Image Processing Efficiency—0
RemoteTrimmer: Adaptive Structural Pruning for Remote Sensing Image ClassificationCode0
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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