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 6901–6950 of 10420 papers

TitleStatusHype
Bayesian Optimization for Hyperparameters Tuning in Neural Networks—0
An Adaptive Sampling and Edge Detection Approach for Encoding Static Images for Spiking Neural Networks—0
Adaptive Region Pooling for Fine-Grained Representation Learning—0
Label-efficient Single Photon Images Classification via Active Learning—0
DeepRepair: Style-Guided Repairing for DNNs in the Real-world Operational Environment—0
Label-Efficient Group Robustness via Out-of-Distribution Concept Curation—0
Label Denoising through Cross-Model Agreement—0
Deep-Relative-Trust-Based Diffusion for Decentralized Deep Learning—0
Label Consistent Transform Learning for Hyperspectral Image Classification—0
Not all Failure Modes are Created Equal: Training Deep Neural Networks for Explicable (Mis)Classification—0
Deep reinforcement learning with automated label extraction from clinical reports accurately classifies 3D MRI brain volumes—0
Deep Reinforcement Learning using Capsules in Advanced Game Environments—0
KTAN: Knowledge Transfer Adversarial Network—0
Deep Reinforcement Learning for Task Offloading in UAV-Aided Smart Farm Networks—0
Deep reinforcement learning-based image classification achieves perfect testing set accuracy for MRI brain tumors with a training set of only 30 images—0
Kolmogorov-Arnold networks for metal surface defect classification—0
Deep Reinforcement Learning and its Neuroscientific Implications—0
Now You See Me: Robust approach to Partial Occlusions—0
Bayesian Learning to Optimize: Quantifying the Optimizer Uncertainty—0
Adaptive Gradient Regularization: A Faster and Generalizable Optimization Technique for Deep Neural Networks—0
Adaptive Precision Training: Quantify Back Propagation in Neural Networks with Fixed-point Numbers—0
Deep reinforced active learning for multi-class image classification—0
KO: Kinetics-inspired Neural Optimizer with PDE Simulation Approaches—0
Bayesian Learning-driven Prototypical Contrastive Loss for Class-Incremental Learning—0
Knowledge Representing: Efficient, Sparse Representation of Prior Knowledge for Knowledge Distillation—0
Deep Quantization: Encoding Convolutional Activations with Deep Generative Model—0
Bayesian Layer Graph Convolutioanl Network for Hyperspetral Image Classification—0
Object-Centric Representation Learning from Unlabeled Videos—0
Knowledge Graph Embeddings for Multi-Lingual Structured Representations of Radiology Reports—0
Categorical Knowledge Fused Recognition: Fusing Hierarchical Knowledge with Image Classification through Aligning and Deep Metric Learning—0
EA-KD: Entropy-based Adaptive Knowledge Distillation—0
Object Detection on Single Monocular Images through Canonical Correlation Analysis—0
DeepPSL: End-to-end perception and reasoning—0
Object-Level Representation Learning for Few-Shot Image Classification—0
Bayesian Inference for Large Scale Image Classification—0
Knowledge-Free Black-Box Watermark and Ownership Proof for Image Classification Neural Networks—0
Object-oriented backdoor attack against image captioning—0
Knowledge-Embedded Representation Learning for Fine-Grained Image Recognition—0
Representative Teacher Keys for Knowledge Distillation Model Compression Based on Attention Mechanism for Image Classification—0
Knowledge Distillation with Feature Maps for Image Classification—0
Bayesian Federated Neural Matching that Completes Full Information—0
An Access Control Method with Secret Key for Semantic Segmentation Models—0
Adaptive Periodic Averaging: A Practical Approach to Reducing Communication in Distributed Learning—0
Achieving Explainability in a Visual Hard Attention Model through Content Prediction—0
KOALA++: Efficient Kalman-Based Optimization of Neural Networks with Gradient-Covariance Products—0
Occupancy Detection in Vehicles Using Fisher Vector Image Representation—0
Knowledge distillation using unlabeled mismatched images—0
Knowledge Distillation Methods for Efficient Unsupervised Adaptation Across Multiple Domains—0
Knowledge Distillation in Vision Transformers: A Critical Review—0
Deep Predictive Coding Network for Object Recognition—0
Show:102550
← PrevPage 139 of 209Next →
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