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 90019025 of 10420 papers

TitleStatusHype
Examining the Proximity of Adversarial Examples to Class Manifolds in Deep Networks0
Example-Based Explainable AI and its Application for Remote Sensing Image Classification0
Exemplar Based Deep Discriminative and Shareable Feature Learning for Scene Image Classification0
Exemplar-free Online Continual Learning0
Exemplar SVMs as Visual Feature Encoders0
ExMobileViT: Lightweight Classifier Extension for Mobile Vision Transformer0
Expanding Training Data for Endoscopic Phenotyping of Eosinophilic Esophagitis0
ExpandNets: Linear Over-parameterization to Train Compact Convolutional Networks0
Experimental Observations of the Topology of Convolutional Neural Network Activations0
Expert-Like Reparameterization of Heterogeneous Pyramid Receptive Fields in Efficient CNNs for Fair Medical Image Classification0
Experts Don't Cheat: Learning What You Don't Know By Predicting Pairs0
Explainability-aided Domain Generalization for Image Classification0
Explainability and Robustness of Deep Visual Classification Models0
Explainable 3D Convolutional Neural Networks by Learning Temporal Transformations0
EXPLAINABLE AI-BASED DYNAMIC FILTER PRUNING OF CONVOLUTIONAL NEURAL NETWORKS0
Explainable AI for medical imaging: Explaining pneumothorax diagnoses with Bayesian Teaching0
Explainable AI (XAI) in Image Segmentation in Medicine, Industry, and Beyond: A Survey0
Explainable Analysis of Deep Learning Methods for SAR Image Classification0
Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models0
Explainable Disease Classification via weakly-supervised segmentation0
Explainable Image Classification with Evidence Counterfactual0
Explainable Knowledge Distillation for On-device Chest X-Ray Classification0
Explainable Metric Learning for Deflating Data Bias0
Explainable unsupervised multi-modal image registration using deep networks0
Explainers in the Wild: Making Surrogate Explainers Robust to Distortions through Perception0
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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
5DaViT-HTop 1 Accuracy90.2Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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