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 651–700 of 10419 papers

TitleStatusHype
Augmentation Strategies for Learning with Noisy LabelsCode1
Deblurring Masked Autoencoder is Better Recipe for Ultrasound Image RecognitionCode1
AMC-Loss: Angular Margin Contrastive Loss for Improved Explainability in Image ClassificationCode1
Adaptive DropBlock Enhanced Generative Adversarial Networks for Hyperspectral Image ClassificationCode1
Augmented Neural ODEsCode1
Augmented Neural Fine-Tuning for Efficient Backdoor PurificationCode1
Adaptive Edge Offloading for Image Classification Under Rate LimitCode1
Augmenting Convolutional networks with attention-based aggregationCode1
Attention-Gated Brain Propagation: How the brain can implement reward-based error backpropagationCode1
Deep AutoAugmentCode1
AugNet: End-to-End Unsupervised Visual Representation Learning with Image AugmentationCode1
AugMix: A Simple Data Processing Method to Improve Robustness and UncertaintyCode1
AutoDC: Automated data-centric processingCode1
Deep CORAL: Correlation Alignment for Deep Domain AdaptationCode1
Deep Factorized Metric LearningCode1
Deep Fast Vision: Accelerated Deep Transfer Learning Vision Prototyping and BeyondCode1
A Universal Representation Transformer Layer for Few-Shot Image ClassificationCode1
DeepGleason: a System for Automated Gleason Grading of Prostate Cancer using Deep Neural NetworksCode1
Domain Prompt Learning for Efficiently Adapting CLIP to Unseen DomainsCode1
AutoDiCE: Fully Automated Distributed CNN Inference at the EdgeCode1
DataMUX: Data Multiplexing for Neural NetworksCode1
Automated detection of COVID-19 cases from chest X-ray images using deep neural network and XGBoostCode1
DCN-T: Dual Context Network with Transformer for Hyperspectral Image ClassificationCode1
DeepNoise: Signal and Noise Disentanglement based on Classifying Fluorescent Microscopy Images via Deep LearningCode1
Adaptive Mask Sampling and Manifold to Euclidean Subspace Learning with Distance Covariance Representation for Hyperspectral Image ClassificationCode1
AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on the FlyCode1
Deep Multimodal Guidance for Medical Image ClassificationCode1
Deep Reinforcement Learning for Band Selection in Hyperspectral Image ClassificationCode1
AdaptiveMix: Improving GAN Training via Feature Space ShrinkageCode1
Deep Semantic-Visual Alignment for Zero-Shot Remote Sensing Image Scene ClassificationCode1
Automated Learning Rate Scheduler for Large-batch TrainingCode1
Automated Relational Meta-learningCode1
UniUSNet: A Promptable Framework for Universal Ultrasound Disease Prediction and Tissue SegmentationCode1
Deep Unlearning: Fast and Efficient Gradient-free Approach to Class ForgettingCode1
DeepVoxNet2: Yet another CNN frameworkCode1
Automatically designing CNN architectures using genetic algorithm for image classificationCode1
On Creating Benchmark Dataset for Aerial Image Interpretation: Reviews, Guidances and Million-AIDCode1
AutoMix: Unveiling the Power of Mixup for Stronger ClassifiersCode1
Automating Continual LearningCode1
A Visual Analytics Framework for Explaining and Diagnosing Transfer Learning ProcessesCode1
Achieving Fairness Through Channel Pruning for Dermatological Disease DiagnosisCode1
Demonstrating the Efficacy of Kolmogorov-Arnold Networks in Vision TasksCode1
Adaptive Token Sampling For Efficient Vision TransformersCode1
Dendritic Learning-incorporated Vision Transformer for Image RecognitionCode1
Attack of the Tails: Yes, You Really Can Backdoor Federated LearningCode1
data2vec: A General Framework for Self-supervised Learning in Speech, Vision and LanguageCode1
Adaptive Risk Minimization: Learning to Adapt to Domain ShiftCode1
Depth Uncertainty in Neural NetworksCode1
Averaging Weights Leads to Wider Optima and Better GeneralizationCode1
Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODECode1
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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