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

Showing 27262750 of 10420 papers

TitleStatusHype
Improving singing voice separation with the Wave-U-Net using Minimum Hyperspherical EnergyCode0
BRIDLE: Generalized Self-supervised Learning with QuantizationCode0
A New Cervical Cytology Dataset for Nucleus Detection and Image Classification (Cervix93) and Methods for Cervical Nucleus DetectionCode0
A Design Methodology for Efficient Implementation of Deconvolutional Neural Networks on an FPGACode0
Bridging Sensor Gaps via Attention Gated Tuning for Hyperspectral Image ClassificationCode0
An Evolutionary Approach to Dynamic Introduction of Tasks in Large-scale Multitask Learning SystemsCode0
Improving Pre-Trained Weights Through Meta-Heuristics Fine-TuningCode0
Improving Prototypical Visual Explanations with Reward Reweighing, Reselection, and RetrainingCode0
Improving Random-Sampling Neural Architecture Search by Evolving the Proxy Search SpaceCode0
Improving robustness to corruptions with multiplicative weight perturbationsCode0
Improving the trustworthiness of image classification models by utilizing bounding-box annotationsCode0
Improving Neural Architecture Search Image Classifiers via Ensemble LearningCode0
A Coefficient Makes SVRG EffectiveCode0
Breast-NET: a lightweight DCNN model for breast cancer detection and grading using histological samplesCode0
Improving model calibration with accuracy versus uncertainty optimizationCode0
Improving Nonlinear Projection Heads using Pretrained Autoencoder EmbeddingsCode0
Breast cancer image classification on WSI with spatial correlationsCode0
A Deep Neuro-Fuzzy Network for Image ClassificationCode0
A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection in Network Traffic DataCode0
Improving Memory Efficiency for Training KANs via Meta LearningCode0
SynerMix: Synergistic Mixup Solution for Enhanced Intra-Class Cohesion and Inter-Class Separability in Image ClassificationCode0
3D-Convolution Guided Spectral-Spatial Transformer for Hyperspectral Image ClassificationCode0
Improving Intervention Efficacy via Concept Realignment in Concept Bottleneck ModelsCode0
Improving Generalization of Batch Whitening by Convolutional Unit OptimizationCode0
Improving k-Means Clustering Performance with Disentangled Internal RepresentationsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
6DaViT-HTop 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10RevCol-HTop 1 Accuracy90Unverified