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 6601–6650 of 10420 papers

TitleStatusHype
QFCNN: Quantum Fourier Convolutional Neural Network—0
CapsuleRRT: Relationships-Aware Regression Tracking via Capsules—0
Distribution-Aware Adaptive Multi-Bit Quantization—0
MaxUp: Lightweight Adversarial Training With Data Augmentation Improves Neural Network Training—0
Boosting Ensemble Accuracy by Revisiting Ensemble Diversity MetricsCode0
Informative Class Activation Maps—0
Practical Transferability Estimation for Image Classification Tasks—0
Hilbert Sinkhorn Divergence for Optimal Transport—0
Cross Modality Knowledge Distillation for Multi-Modal Aerial View Object ClassificationCode0
Quality-Agnostic Image Recognition via Invertible DecoderCode0
Spatial Assembly Networks for Image Representation Learning—0
Teacher's pet: understanding and mitigating biases in distillation—0
Self-Supervised Wasserstein Pseudo-Labeling for Semi-Supervised Image Classification—0
Certified robustness against adversarial patch attacks via randomized cropping—0
Effective Model Sparsification by Scheduled Grow-and-Prune MethodsCode0
Light Lies: Optical Adversarial Attack—0
Quantized Neural Networks via -1, +1 Encoding Decomposition and AccelerationCode0
Defending Adversaries Using Unsupervised Feature Clustering VAE—0
Residual Error: a New Performance Measure for Adversarial Robustness—0
ShuffleBlock: Shuffle to Regularize Deep Convolutional Neural Networks—0
Evaluating the Robustness of Bayesian Neural Networks Against Different Types of Attacks—0
MetaBalance: High-Performance Neural Networks for Class-Imbalanced Data—0
Deep reinforcement learning with automated label extraction from clinical reports accurately classifies 3D MRI brain volumes—0
ParticleAugment: Sampling-Based Data Augmentation—0
Effective Evaluation of Deep Active Learning on Image Classification Tasks—0
Disentangling Semantic-to-visual Confusion for Zero-shot LearningCode0
DeepSplit: Scalable Verification of Deep Neural Networks via Operator SplittingCode0
Structured DropConnect for Uncertainty Inference in Image ClassificationCode0
Input Invex Neural NetworkCode0
Robust Training in High Dimensions via Block Coordinate Geometric Median DescentCode0
Revisiting the Calibration of Modern Neural NetworksCode0
Zero-sample surface defect detection and classification based on semantic feedback neural network—0
A Lightweight ReLU-Based Feature Fusion for Aerial Scene Classification—0
Test Sample Accuracy Scales with Training Sample Density in Neural NetworksCode0
Contextualizing Meta-Learning via Learning to DecomposeCode0
Computer-aided Interpretable Features for Leaf Image ClassificationCode0
NG+ : A Multi-Step Matrix-Product Natural Gradient Method for Deep LearningCode0
Survey: Image Mixing and Deleting for Data AugmentationCode0
An Interaction-based Convolutional Neural Network (ICNN) Towards Better Understanding of COVID-19 X-ray ImagesCode0
DMSANet: Dual Multi Scale Attention Network—0
On-Off Center-Surround Receptive Fields for Accurate and Robust Image ClassificationCode0
NDPNet: A novel non-linear data projection network for few-shot fine-grained image classification—0
MRSCAtt: A Spatio-Channel Attention-Guided Network for Mars Rover Image ClassificationCode0
Disrupting Model Training with Adversarial Shortcuts—0
Comparative Investigation of Learning Algorithms for Image Classification with Small Dataset—0
Monotonic Neural Network: combining Deep Learning with Domain Knowledge for Chiller Plants Energy Optimization—0
Scale-invariant scale-channel networks: Deep networks that generalise to previously unseen scales—0
Differentially Private Federated Learning via Inexact ADMM—0
Spectral Unsupervised Domain Adaptation for Visual Recognition—0
Decoupled Greedy Learning of CNNs for Synchronous and Asynchronous Distributed Learning—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