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 32763300 of 10420 papers

TitleStatusHype
Deep Multi-View Spatial-Temporal Network for Taxi Demand PredictionCode0
BASS Net: Band-Adaptive Spectral-Spatial Feature Learning Neural Network for Hyperspectral Image ClassificationCode0
Improving Ensemble Distillation With Weight Averaging and Diversifying PerturbationCode0
Improving Fairness in Image Classification via SketchingCode0
3D Wavelet Convolutions with Extended Receptive Fields for Hyperspectral Image ClassificationCode0
Improving Confident-Classifiers For Out-of-distribution DetectionCode0
An In-Depth Analysis of Adversarial Discriminative Domain Adaptation for Digit ClassificationCode0
Improving Calibration by Relating Focal Loss, Temperature Scaling, and PropernessCode0
Adaptive Meta-Learning for Identification of Rover-Terrain DynamicsCode0
Improving Classification Neural Networks by using Absolute activation function (MNIST/LeNET-5 example)Code0
Improving Deep Neural Network Random Initialization Through Neuronal RewiringCode0
Deep Multimodality Model for Multi-task Multi-view LearningCode0
A Multimodal Approach For Endoscopic VCE Image Classification Using BiomedCLIP-PubMedBERTCode0
Deep Modeling and Optimization of Medical Image ClassificationCode0
Towards Difficulty-Agnostic Efficient Transfer Learning for Vision-Language ModelsCode0
Deep Metric Learning-Based Feature Embedding for Hyperspectral Image ClassificationCode0
Understanding and Robustifying Differentiable Architecture SearchCode0
Improving (α, f)-Byzantine Resilience in Federated Learning via layerwise aggregation and cosine distanceCode0
Improving Generalizability of Kolmogorov-Arnold Networks via Error-Correcting Output CodesCode0
Deep Manifold Embedding for Hyperspectral Image ClassificationCode0
Dynamic 3D KAN Convolution with Adaptive Grid Optimization for Hyperspectral Image ClassificationCode0
Image Data Augmentation Approaches: A Comprehensive Survey and Future directionsCode0
Dynamic Channel Selection in Self-Supervised LearningCode0
Improved robustness of reinforcement learning policies upon conversion to spiking neuronal network platforms applied to ATARI gamesCode0
Improved Training Speed, Accuracy, and Data Utilization Through Loss Function OptimizationCode0
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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