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 7851–7900 of 10420 papers

TitleStatusHype
Q-CapsNets: A Specialized Framework for Quantizing Capsule Networks—0
A Hybrid Method for Training Convolutional Neural Networks—0
Stochastic batch size for adaptive regularization in deep network optimization—0
Detached Error Feedback for Distributed SGD with Random Sparsification—0
Exploring Optimal Deep Learning Models for Image-based Malware Variant Classification—0
ASL Recognition with Metric-Learning based Lightweight Network—0
Dithered backprop: A sparse and quantized backpropagation algorithm for more efficient deep neural network training—0
TensorProjection Layer: A Tensor-Based Dimension Reduction Method in Deep Neural NetworksCode0
Empirical Perspectives on One-Shot Semi-supervised Learning—0
Towards Reusable Network Components by Learning Compatible Representations—0
Radon cumulative distribution transform subspace modeling for image classificationCode0
Teacher-Class Network: A Neural Network Compression MechanismCode0
Two-Stage Resampling for Convolutional Neural Network Training in the Imbalanced Colorectal Cancer Image Classification—0
Inspector Gadget: A Data Programming-based Labeling System for Industrial Images—0
Increasing the Inference and Learning Speed of Tsetlin Machines with Clause Indexing—0
Generative Adversarial Zero-shot Learning via Knowledge Graphs—0
Large-scale spatiotemporal photonic reservoir computer for image classification—0
Attribute Mix: Semantic Data Augmentation for Fine Grained Recognition—0
Comparative Analysis of Multiple Deep CNN Models for Waste Classification—0
Approximate Manifold Defense Against Multiple Adversarial PerturbationsCode0
Group Based Deep Shared Feature Learning for Fine-grained Image Classification—0
Generative Adversarial Networks Based on Collaborative Learning and Attention Mechanism for Hyperspectral Image Classification—0
Predicting the outputs of finite deep neural networks trained with noisy gradients—0
Learning Sparse & Ternary Neural Networks with Entropy-Constrained Trained Ternarization (EC2T)Code0
In Automation We Trust: Investigating the Role of Uncertainty in Active Learning Systems—0
Adversarial Learning for Personalized Tag RecommendationCode0
Improving Deep Hyperspectral Image Classification Performance with Spectral Unmixing—0
Incremental Learning In Online Scenario—0
Improved Gradient based Adversarial Attacks for Quantized NetworksCode0
Attentive CutMix: An Enhanced Data Augmentation Approach for Deep Learning Based Image Classification—0
Applications of the Streaming Networks—0
Classification of Chinese Handwritten Numbers with Labeled Projective Dictionary Pair Learning—0
Neural encoding and interpretation for high-level visual cortices based on fMRI using image caption features—0
Triad State Space Construction for Chaotic Signal Classification with Deep Learning—0
Milking CowMask for Semi-Supervised Image ClassificationCode0
Strategies for Robust Image Classification—0
Pipelined Backpropagation at Scale: Training Large Models without Batches—0
Covid-19: Automatic detection from X-Ray images utilizing Transfer Learning with Convolutional Neural Networks—0
GreedyNAS: Towards Fast One-Shot NAS with Greedy Supernet—0
Synergic Adversarial Label Learning for Grading Retinal Diseases via Knowledge Distillation and Multi-task Learning—0
Robust and On-the-fly Dataset Denoising for Image Classification—0
Surface Damage Detection Scheme using Convolutional Neural Network and Artificial Neural Network—0
Performance Evaluation of Low-Cost Machine Vision Cameras for Image-Based Grasp VerificationCode0
SAC: Accelerating and Structuring Self-Attention via Sparse Adaptive Connection—0
HDF: Hybrid Deep Features for Scene Image Representation—0
TanhExp: A Smooth Activation Function with High Convergence Speed for Lightweight Neural Networks—0
Dynamic Sampling and Selective Masking for Communication-Efficient Federated Learning—0
Fine-grained Species Recognition with Privileged Pooling: Better Sample Efficiency Through Supervised AttentionCode0
Event-Based Control for Online Training of Neural Networks—0
Affinity Graph Supervision for Visual Recognition—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