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 8001–8025 of 10420 papers

TitleStatusHype
Improvement of image classification by multiple optical scattering—0
ResNetX: a more disordered and deeper network architecture—0
Resolution-Based Distillation for Efficient Histology Image Classification—0
Deep AUC Maximization for Medical Image Classification: Challenges and Opportunities—0
REFT: Resource-Efficient Federated Training Framework for Heterogeneous and Resource-Constrained Environments—0
Resource Efficient Neural Networks Using Hessian Based Pruning—0
Automatic Radiology Report Generation based on Multi-view Image Fusion and Medical Concept Enrichment—0
Identify ambiguous tasks combining crowdsourced labels by weighting Areas Under the Margin—0
Improved Training Speed, Accuracy, and Data Utilization via Loss Function Optimization—0
Deep Attributes from Context-Aware Regional Neural Codes—0
Restricted Boltzmann Machines for galaxy morphology classification with a quantum annealer—0
RE-Tagger: A light-weight Real-Estate Image Classifier—0
RetailKLIP : Finetuning OpenCLIP backbone using metric learning on a single GPU for Zero-shot retail product image classification—0
Retaining Knowledge and Enhancing Long-Text Representations in CLIP through Dual-Teacher Distillation—0
Improved Trainable Calibration Method for Neural Networks on Medical Imaging Classification—0
Rethinking and Improving Relative Position Encoding for Vision Transformer—0
Improved texture image classification through the use of a corrosion-inspired cellular automaton—0
Deep Algorithmic Question Answering: Towards a Compositionally Hybrid AI for Algorithmic Reasoning—0
Improved Text Classification via Test-Time Augmentation—0
Improved Robustness of Vision Transformer via PreLayerNorm in Patch Embedding—0
DeepAGREL: Biologically plausible deep learning via direct reinforcement—0
Rethinking Crowdsourcing Annotation: Partial Annotation with Salient Labels for Multi-Label Image Classification—0
Automatic estimation of heading date of paddy rice using deep learning—0
A Local Detection Approach for Named Entity Recognition and Mention Detection—0
Between Progress and Potential Impact of AI: the Neglected Dimensions—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
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified