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 36013625 of 10420 papers

TitleStatusHype
Deep Combinatorial AggregationCode0
PUNCH: Positive UNlabelled Classification based information retrieval in Hyperspectral imagesCode0
Evaluating Defensive Distillation For Defending Text Processing Neural Networks Against Adversarial ExamplesCode0
ImageNet Classification with Deep Convolutional Neural NetworksCode0
ImageNot: A contrast with ImageNet preserves model rankingsCode0
Inductive biases of multi-task learning and finetuning: multiple regimes of feature reuseCode0
Learning Curves for Noisy Heterogeneous Feature-Subsampled Ridge EnsemblesCode0
MetH: A family of high-resolution and variable-shape image challengesCode0
Image Classification with Classic and Deep Learning TechniquesCode0
Deep CNN-based Multi-task Learning for Open-Set RecognitionCode0
Image Classification with CondenseNeXt for ARM-Based Computing PlatformsCode0
Image Classification Using Singular Value Decomposition and OptimizationCode0
Deep Categorization with Semi-Supervised Self-Organizing MapsCode0
Automatic Recognition of Learning Resource Category in a Digital LibraryCode0
Image classification in frequency domain with 2SReLU: a second harmonics superposition activation functionCode0
Deep Bayesian segmentation for colon polyps: Well-calibrated predictions in medical imagingCode0
Classifying a specific image region using convolutional nets with an ROI mask as inputCode0
Ensemble learning in CNN augmented with fully connected subnetworksCode0
Classifying high-dimensional Gaussian mixtures: Where kernel methods fail and neural networks succeedCode0
Quantitative Analysis of Primary Attribution Explainable Artificial Intelligence Methods for Remote Sensing Image ClassificationCode0
Ensemble of ConvNeXt V2 and MaxViT for Long-Tailed CXR Classification with View-Based AggregationCode0
Adversarial Defense by Suppressing High-frequency ComponentsCode0
Image Classification of Melanoma, Nevus and Seborrheic Keratosis by Deep Neural Network EnsembleCode0
Image Classification with Hierarchical Multigraph NetworksCode0
Automatic Open-World Reliability AssessmentCode0
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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