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 626–650 of 10419 papers

TitleStatusHype
Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component EvaluationCode0
Learned Compression for Compressed LearningCode0
Embeddings are all you need! Achieving High Performance Medical Image Classification through Training-Free Embedding Analysis—0
Revisiting Weight Averaging for Model MergingCode1
Multimodal Approaches to Fair Image Classification: An Ethical Perspective—0
ALoRE: Efficient Visual Adaptation via Aggregating Low Rank Experts—0
Wasserstein Distance Rivals Kullback-Leibler Divergence for Knowledge DistillationCode2
IMPACT: A Large-scale Integrated Multimodal Patent Analysis and Creation Dataset for Design PatentsCode1
Real-time Chest X-Ray Distributed Decision Support for Resource-constrained Clinics—0
Leveraging Content and Context Cues for Low-Light Image EnhancementCode0
Image Classification Using Singular Value Decomposition and OptimizationCode0
An Enhancement of CNN Algorithm for Rice Leaf Disease Image Classification in Mobile Applications—0
Post-Training Non-Uniform Quantization for Convolutional Neural Networks—0
How transfer learning is used in generative models for image classification: improved accuracyCode0
Impact of Privacy Parameters on Deep Learning Models for Image Classification—0
Convolution goes higher-order: a biologically inspired mechanism empowers image classification—0
Vision Transformer-based Semantic Communications With Importance-Aware Quantization—0
Hyperspectral Image Spectral-Spatial Feature Extraction via Tensor Principal Component Analysis—0
Sparse autoencoders reveal selective remapping of visual concepts during adaptationCode1
MTSpark: Enabling Multi-Task Learning with Spiking Neural Networks for Generalist Agents—0
Quantized and Interpretable Learning Scheme for Deep Neural Networks in Classification Task—0
FedDUAL: A Dual-Strategy with Adaptive Loss and Dynamic Aggregation for Mitigating Data Heterogeneity in Federated LearningCode0
Enhancing Whole Slide Image Classification through Supervised Contrastive Domain Adaptation—0
Grounding Descriptions in Images informs Zero-Shot Visual RecognitionCode1
Multisource Collaborative Domain Generalization for Cross-Scene Remote Sensing 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