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 9926–9950 of 10420 papers

TitleStatusHype
Interpreting Equivariant Representations—0
Interpreting Interpretations: Organizing Attribution Methods by Criteria—0
Interpreting the Predictions of Complex ML Models by Layer-wise Relevance Propagation—0
Interpreting Undesirable Pixels for Image Classification on Black-Box Models—0
Interventional Black-Box Explanations—0
Intra-Model Collaborative Learning of Neural Networks—0
Intriguing Frequency Interpretation of Adversarial Robustness for CNNs and ViTs—0
Robustness via Deep Low-Rank Representations—0
Introducing Fuzzy Layers for Deep Learning—0
Introducing the structural bases of typicality effects in deep learning—0
Introduction to Camera Pose Estimation with Deep Learning—0
Introspection for convolutional automatic speech recognition—0
Intrusion Detection: Machine Learning Baseline Calculations for Image Classification—0
Intuitionistic Fuzzy Cognitive Maps for Interpretable Image Classification—0
Invariance-Guided Feature Evolution for Few-Shot Learning—0
Invariance vs Robustness of Neural Networks—0
Invariant Attribute Profiles: A Spatial-Frequency Joint Feature Extractor for Hyperspectral Image Classification—0
Invariant Learning via Diffusion Dreamed Distribution Shifts—0
Invariant Scattering Transform for Medical Imaging—0
Inverse-Free Fast Natural Gradient Descent Method for Deep Learning—0
Inverted Semantic-Index for Image Retrieval—0
Inverting The Generator Of A Generative Adversarial Network—0
Investigating a Baseline Of Self Supervised Learning Towards Reducing Labeling Costs For Image Classification—0
Investigating Bias in Image Classification using Model Explanations—0
Investigating Calibration and Corruption Robustness of Post-hoc Pruned Perception CNNs: An Image Classification Benchmark Study—0
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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
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified