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 7101–7150 of 10420 papers

TitleStatusHype
Keeping Representation Similarity in Finetuning for Medical Image Analysis—0
Deep Neural Networks—0
KCRC-LCD: Discriminative Kernel Collaborative Representation with Locality Constrained Dictionary for Visual Categorization—0
Deep Neural Network Models Trained With A Fixed Random Classifier Transfer Better Across Domains—0
On the performance of residual block design alternatives in convolutional neural networks for end-to-end audio classification—0
A Multiresolution Clinical Decision Support System Based on Fractal Model Design for Classification of Histological Brain Tumours—0
Adaptive Mixture of Low-Rank Factorizations for Compact Neural Modeling—0
On the rate of convergence of image classifiers based on convolutional neural networks—0
KANs for Computer Vision: An Experimental Study—0
On the Reproducibility of Neural Network Predictions—0
Deep neural network loses attention to adversarial images—0
On the Robustness of Kolmogorov-Arnold Networks: An Adversarial Perspective—0
On the Robustness of Large Multimodal Models Against Image Adversarial Attacks—0
KAN-Mixers: a new deep learning architecture for image classification—0
Batch Kalman Normalization: Towards Training Deep Neural Networks with Micro-Batches—0
Deep Neural Network Based Hyperspectral Pixel Classification With Factorized Spectral-Spatial Feature Representation—0
On the Sampling Strategy for Evaluation of Spectral-spatial Methods in Hyperspectral Image Classification—0
On the Shift Invariance of Max Pooling Feature Maps in Convolutional Neural Networks—0
Batch Group Normalization—0
On the Surprising Effectiveness of Transformers in Low-Labeled Video Recognition—0
Just rotate it! Uncertainty estimation in closed-source models via multiple queries—0
On the Transferability of Adversarial Examples between Encrypted Models—0
On the universality of neural encodings in CNNs—0
On the unreasonable vulnerability of transformers for image restoration -- and an easy fix—0
Just Rotate it: Deploying Backdoor Attacks via Rotation Transformation—0
Just Noticeable Difference for Machine Perception and Generation of Regularized Adversarial Images with Minimal Perturbation—0
Just Leaf It: Accelerating Diffusion Classifiers with Hierarchical Class Pruning—0
Ontology-based n-ball Concept Embeddings Informing Few-shot Image Classification—0
Deep Neural Network Approximation Theory—0
Judge Like a Real Doctor: Dual Teacher Sample Consistency Framework for Semi-supervised Medical Image Classification—0
Joint Source-Channel Coding for Channel-Adaptive Digital Semantic Communications—0
Joint Sensing and Task-Oriented Communications with Image and Wireless Data Modalities for Dynamic Spectrum Access—0
Deep Networks with Fast Retraining—0
Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering—0
A Multi-Modal Multilingual Benchmark for Document Image Classification—0
OOD Augmentation May Be at Odds with Open-Set Recognition—0
OOD-CV-v2: An extended Benchmark for Robustness to Out-of-Distribution Shifts of Individual Nuisances in Natural Images—0
Achieving 3D Attention via Triplet Squeeze and Excitation Block—0
Recent Advances in Medical Image Classification—0
Joint Projection and Dictionary Learning using Low-rank Regularization and Graph Constraints—0
Joint Learning of Set Cardinality and State Distribution—0
Joint Learning of Neural Transfer and Architecture Adaptation for Image Recognition—0
Deep Multi-view Models for Glitch Classification—0
Joint Learning of Discriminative Low-dimensional Image Representations Based on Dictionary Learning and Two-layer Orthogonal Projections—0
Joint Intermodal and Intramodal Label Transfers for Extremely Rare or Unseen Classes—0
Deep Multi-View Learning using Neuron-Wise Correlation-Maximizing Regularizers—0
A Multi-Modal Federated Learning Framework for Remote Sensing Image Classification—0
Joint Hierarchical Category Structure Learning and Large-Scale Image Classification—0
Open Set Learning with Counterfactual Images—0
Deep Multi-Task Learning for Malware 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