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

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Showing 4776–4800 of 10420 papers

TitleStatusHype
Fast and Accurate Inference with Adaptive Ensemble Prediction for Deep Networks—0
Communication-Efficient Federated Distillation—0
A review: Deep learning for medical image segmentation using multi-modality fusion—0
Fast Adaptation with Linearized Neural Networks—0
Fast Adaptation with Bradley-Terry Preference Models in Text-To-Image Classification and Generation—0
FastAdaBelief: Improving Convergence Rate for Belief-based Adaptive Optimizers by Exploiting Strong Convexity—0
Communication-Efficient Edge AI: Algorithms and Systems—0
High-performance deep spiking neural networks with 0.3 spikes per neuron—0
AdvJND: Generating Adversarial Examples with Just Noticeable Difference—0
A Control Theoretic Framework for Adaptive Gradient Optimizers in Machine Learning—0
Fashion CUT: Unsupervised domain adaptation for visual pattern classification in clothes using synthetic data and pseudo-labels—0
Fashion and Apparel Classification using Convolutional Neural Networks—0
Communication-Efficient Adaptive Batch Size Strategies for Distributed Local Gradient Methods—0
Fantope Regularization in Metric Learning—0
Communication-Computation Efficient Device-Edge Co-Inference via AutoML—0
Fall Leaf Adversarial Attack on Traffic Sign Classification—0
FALIP: Visual Prompt as Foveal Attention Boosts CLIP Zero-Shot Performance—0
Exploring the Interchangeability of CNN Embedding Spaces—0
Committees of deep feedforward networks trained with few data—0
Comment on "Ensemble Projection for Semi-supervised Image Classification"—0
Fair-VPT: Fair Visual Prompt Tuning for Image Classification—0
FairSAM: Fair Classification on Corrupted Data Through Sharpness-Aware Minimization—0
Combining Stochastic Defenses to Resist Gradient Inversion: An Ablation Study—0
FairREAD: Re-fusing Demographic Attributes after Disentanglement for Fair Medical Image Classification—0
FairPrune: Achieving Fairness Through Pruning for Dermatological Disease Diagnosis—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
10RevCol-HTop 1 Accuracy90—Unverified