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 6901–6925 of 10420 papers

TitleStatusHype
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
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
Not all Failure Modes are Created Equal: Training Deep Neural Networks for Explicable (Mis)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
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
Now You See Me: Robust approach to Partial Occlusions—0
EA-KD: Entropy-based Adaptive Knowledge Distillation—0
DeepPSL: End-to-end perception and reasoning—0
Bayesian Inference for Large Scale Image Classification—0
Knowledge-Free Black-Box Watermark and Ownership Proof for Image Classification Neural Networks—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
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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