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 7601–7625 of 10420 papers

TitleStatusHype
Improved Gradient based Adversarial Attacks for Quantized NetworksCode0
Attentive CutMix: An Enhanced Data Augmentation Approach for Deep Learning Based Image Classification—0
Applications of the Streaming Networks—0
GAN-based Priors for Quantifying UncertaintyCode1
Convolutional Spiking Neural Networks for Spatio-Temporal Feature ExtractionCode1
Strategies for Robust Image Classification—0
Classification of Chinese Handwritten Numbers with Labeled Projective Dictionary Pair Learning—0
Neural encoding and interpretation for high-level visual cortices based on fMRI using image caption features—0
Milking CowMask for Semi-Supervised Image ClassificationCode0
Triad State Space Construction for Chaotic Signal Classification with Deep Learning—0
Hit-Detector: Hierarchical Trinity Architecture Search for Object DetectionCode1
Pipelined Backpropagation at Scale: Training Large Models without Batches—0
Circumventing Outliers of AutoAugment with Knowledge DistillationCode1
Rethinking Few-Shot Image Classification: a Good Embedding Is All You Need?Code1
Covid-19: Automatic detection from X-Ray images utilizing Transfer Learning with Convolutional Neural Networks—0
GreedyNAS: Towards Fast One-Shot NAS with Greedy Supernet—0
Robust and On-the-fly Dataset Denoising for Image Classification—0
Synergic Adversarial Label Learning for Grading Retinal Diseases via Knowledge Distillation and Multi-task Learning—0
Surface Damage Detection Scheme using Convolutional Neural Network and Artificial Neural Network—0
Meta Pseudo LabelsCode1
Performance Evaluation of Low-Cost Machine Vision Cameras for Image-Based Grasp VerificationCode0
TanhExp: A Smooth Activation Function with High Convergence Speed for Lightweight Neural Networks—0
SAC: Accelerating and Structuring Self-Attention via Sparse Adaptive Connection—0
HDF: Hybrid Deep Features for Scene Image Representation—0
Adversarial Continual LearningCode1
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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