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 5251–5300 of 10420 papers

TitleStatusHype
Grouped Pointwise Convolutions Significantly Reduces Parameters in EfficientNetCode0
FocusNet: Classifying Better by Focusing on Confusing ClassesCode1
Non-deep NetworksCode1
Self-Supervised Learning by Estimating Twin Class DistributionsCode1
Adversarial Attack across Datasets—0
Scaling Laws for the Few-Shot Adaptation of Pre-trained Image Classifiers—0
Subspace Regularizers for Few-Shot Class Incremental LearningCode1
Well-classified Examples are Underestimated in Classification with Deep Neural NetworksCode1
Transform and Bitstream Domain Image Classification—0
Bio-inspired learnable divisive normalization for ANNs—0
Dynamic Inference with Neural Interpreters—0
NAS-Bench-360: Benchmarking Neural Architecture Search on Diverse TasksCode1
Balancing Average and Worst-case Accuracy in Multitask Learning—0
CovXR: Automated Detection of COVID-19 Pneumonia in Chest X-Rays through Machine Learning—0
Voice-assisted Image Labelling for Endoscopic Ultrasound Classification using Neural Networks—0
Semi-Supervised Auto-Encoder Graph Network for Diabetic Retinopathy Grading—0
Decomposing Convolutional Neural Networks into Reusable and Replaceable Modules—0
A Closer Look at Prototype Classifier for Few-shot Image Classification—0
Revitalizing CNN Attentions via Transformers in Self-Supervised Visual Representation LearningCode1
Instance-based Label Smoothing For Better Calibrated Classification NetworksCode0
Synthesizing Machine Learning Programs with PAC Guarantees via Statistical Sketching—0
Learnable Adaptive Cosine Estimator (LACE) for Image ClassificationCode0
Homogeneous Learning: Self-Attention Decentralized Deep LearningCode0
Momentum Centering and Asynchronous Update for Adaptive Gradient MethodsCode2
Heavy Ball Neural Ordinary Differential EquationsCode1
Class-Balanced Active Learning for Image ClassificationCode1
DenseNet approach to segmentation and classification of dermatoscopic skin lesions imagesCode0
Automatic Recognition of Abdominal Organs in Ultrasound Images based on Deep Neural Networks and K-Nearest-Neighbor ClassificationCode1
SGMNet: Scene Graph Matching Network for Few-Shot Remote Sensing Scene Classification—0
A Genetic Programming Approach To Zero-Shot Neural Architecture Ranking—0
PAC Synthesis of Machine Learning Programs—0
Image Compression and Classification Using Qubits and Quantum Deep Learning—0
UniNet: Unified Architecture Search with Convolution, Transformer, and MLP—0
ViDT: An Efficient and Effective Fully Transformer-based Object Detector—0
Observations on K-image Expansion of Image-Mixing Augmentation for ClassificationCode0
Using Contrastive Learning and Pseudolabels to learn representations for Retail Product Image Classification—0
Reliable Probability Intervals For Classification Using Inductive Venn Predictors Based on Distance Learning—0
MSHCNet: Multi-Stream Hybridized Convolutional Networks with Mixed Statistics in Euclidean/Non-Euclidean Spaces and Its Application to Hyperspectral Image Classification—0
Test-time Batch Statistics Calibration for Covariate Shift—0
On the Privacy Risks of Deploying Recurrent Neural Networks in Machine Learning Models—0
Weak Novel Categories without Tears: A Survey on Weak-Shot LearningCode1
Deep Transfer Learning for Land Use and Land Cover Classification: A Comparative StudyCode1
Spectral Bias in Practice: The Role of Function Frequency in Generalization—0
On the Importance of Firth Bias Reduction in Few-Shot ClassificationCode1
Seed Classification using Synthetic Image Datasets Generated from Low-Altitude UAV Imagery—0
Adversarial Attacks on Black Box Video Classifiers: Leveraging the Power of Geometric TransformationsCode0
MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision TransformerCode2
WDCCNet: Weighted Double-Classifier Constraint Neural Network for Mammographic Image Classification—0
HYPPO: A Surrogate-Based Multi-Level Parallelism Tool for Hyperparameter Optimization—0
Effectiveness of Optimization Algorithms in Deep Image ClassificationCode0
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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