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 1037610400 of 10420 papers

TitleStatusHype
SIDDA: SInkhorn Dynamic Domain Adaptation for Image Classification with Equivariant Neural NetworksCode0
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile DevicesCode0
Stochastic Deep Networks with Linear Competing Units for Model-Agnostic Meta-LearningCode0
S-TLLR: STDP-inspired Temporal Local Learning Rule for Spiking Neural NetworksCode0
Shorten Spatial-spectral RNN with Parallel-GRU for Hyperspectral Image ClassificationCode0
Understanding the Impact of Label Granularity on CNN-based Image ClassificationCode0
XOOD: Extreme Value Based Out-Of-Distribution Detection For Image ClassificationCode0
SELFIE: Refurbishing Unclean Samples for Robust Deep LearningCode0
Steganographic Embeddings as an Effective Data AugmentationCode0
Understanding the Robustness of Randomized Feature Defense Against Query-Based Adversarial AttacksCode0
Statistical Measures For Defining Curriculum Scoring FunctionCode0
Understanding the Role of Mixup in Knowledge Distillation: An Empirical StudyCode0
Understanding Training-Data Leakage from Gradients in Neural Networks for Image ClassificationCode0
Statistical Loss and Analysis for Deep Learning in Hyperspectral Image ClassificationCode0
Underwater SONAR Image Classification and Analysis using LIME-based Explainable Artificial IntelligenceCode0
UNEM: UNrolled Generalized EM for Transductive Few-Shot LearningCode0
Visual Attention Consistency Under Image Transforms for Multi-Label Image ClassificationCode0
Shortcut Learning in Medical Image SegmentationCode0
ZoDIAC: Zoneout Dropout Injection Attention CalculationCode0
Scalable Framework for Classifying AI-Generated Content Across ModalitiesCode0
Statistical Guarantees for the Robustness of Bayesian Neural NetworksCode0
UniFed: A Universal Federation of a Mixture of Highly Heterogeneous Medical Image Classification TasksCode0
Stateless Neural Meta-Learning using Second-Order GradientsCode0
Star algorithm for NN ensemblingCode0
What do Deep Networks Like to See?Code0
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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