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 9326–9350 of 10420 papers

TitleStatusHype
Frost filtered scale-invariant feature extraction and multilayer perceptron for hyperspectral image classification—0
Frozen Feature Augmentation for Few-Shot Image Classification—0
Efficient Online ML API Selection for Multi-Label Classification Tasks—0
Frugal Reinforcement-based Active Learning—0
Fruit-HSNet: A Machine Learning Approach for Hyperspectral Image-Based Fruit Ripeness Prediction—0
FSNet: Compression of Deep Convolutional Neural Networks by Filter Summary—0
Full-attention based Neural Architecture Search using Context Auto-regression—0
Fully Connected Deep Structured Networks—0
Fully Convolutional Neural Networks to Detect Clinical Dermoscopic Features—0
Fully Hyperbolic Convolutional Neural Networks—0
Function-Space Regularization for Deep Bayesian Classification—0
Function-Space Variational Inference for Deep Bayesian Classification—0
Fundamental Limits of Transfer Learning in Binary Classifications—0
FUNN: Flexible Unsupervised Neural Network—0
FUSECAPS: Investigating Feature Fusion Based Framework for Capsule Endoscopy Image Classification—0
Fusing Deep Convolutional Networks for Large Scale Visual Concept Classification—0
Fusion framework and multimodality for the Laplacian approximation of Bayesian neural networks—0
Fusion of Convolutional Neural Network and Statistical Features for Texture classification—0
Fusion of evidential CNN classifiers for image classification—0
Fusion of Foundation and Vision Transformer Model Features for Dermatoscopic Image Classification—0
Fuzzy-aware Loss for Source-free Domain Adaptation in Visual Emotion Recognition—0
Fuzzy-Based Dialectical Non-Supervised Image Classification and Clustering—0
Fuzzy Pooling—0
Fuzzy Pooling—0
Fuzzy Rank-based Late Fusion Technique for Cytology image Segmentation—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
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
6DaViT-HTop 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