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 4426–4450 of 10420 papers

TitleStatusHype
Identification of Cervical Pathology using Adversarial Neural Networks—0
Identification of Seed Cells in Multispectral Images for GrowCut Segmentation—0
Improved and Explainable Cervical Cancer Classification using Ensemble Pooling of Block Fused Descriptors—0
Deep Learning Classification With Noisy Labels—0
Adaptive Fine-Grained Predicates Learning for Scene Graph Generation—0
Identify Apple Leaf Diseases Using Deep Learning Algorithm—0
Identifying Mislabeled Images in Supervised Learning Utilizing Autoencoder—0
Illuminated Decision Trees with Lucid—0
Deep Learning Benchmarks and Datasets for Social Media Image Classification for Disaster Response—0
Deep learning based prediction of Alzheimer's disease from magnetic resonance images—0
AMLA: an AutoML frAmework for Neural Network Design—0
Deep Learning based Multi-Label Image Classification of Protest Activities—0
Deep Learning based HEp-2 Image Classification: A Comprehensive Review—0
Backpropagation-free Training of Deep Physical Neural Networks—0
I-CNet: Leveraging Involution and Convolution for Image Classification—0
Deep Learning based CNN Model for Classification and Detection of Individuals Wearing Face Mask—0
Deep Learning Based Classification System For Recognizing Local Spinach—0
Amicable Aid: Perturbing Images to Improve Classification Performance—0
ParasNet: Fast Parasites Detection with Neural Networks—0
Backdoor in Seconds: Unlocking Vulnerabilities in Large Pre-trained Models via Model Editing—0
MCU: Improving Machine Unlearning through Mode Connectivity—0
iConFormer: Dynamic Parameter-Efficient Tuning with Input-Conditioned Adaptation—0
Backdoor Embedding in Convolutional Neural Network Models via Invisible Perturbation—0
Deep Learning-based automated classification of Chinese Speech Sound Disorders—0
AMF: Adaptable Weighting Fusion with Multiple Fine-tuning for Image Classification—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