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 7276–7300 of 10420 papers

TitleStatusHype
IrisNet: Deep Learning for Automatic and Real-time Tongue Contour Tracking in Ultrasound Video Data using Peripheral Vision—0
Investigating the Robustness of Vision Transformers against Label Noise in Medical Image Classification—0
PARIC: Probabilistic Attention Regularization for Language Guided Image Classification from Pre-trained Vison Language Models—0
Investigating the Potential of Auxiliary-Classifier GANs for Image Classification in Low Data Regimes—0
CNNs for JPEGs: A Study in Computational Cost—0
Investigating the Catastrophic Forgetting in Multimodal Large Language Models—0
Investigating Calibration and Corruption Robustness of Post-hoc Pruned Perception CNNs: An Image Classification Benchmark Study—0
Investigating Bias in Image Classification using Model Explanations—0
Partial Search in a Frozen Network is Enough to Find a Strong Lottery Ticket—0
Deep Learning Techniques for Geospatial Data Analysis—0
Balance Divergence for Knowledge Distillation—0
ParticleAugment: Sampling-Based Data Augmentation—0
A multicategory jet image classification framework using deep neural network—0
A ChatGPT Aided Explainable Framework for Zero-Shot Medical Image Diagnosis—0
Parting with Illusions about Deep Active Learning—0
CheX-DS: Improving Chest X-ray Image Classification with Ensemble Learning Based on DenseNet and Swin Transformer—0
A Layered Architecture for Active Perception: Image Classification using Deep Reinforcement Learning—0
Pasadena: Perceptually Aware and Stealthy Adversarial Denoise Attack—0
Commit2Vec: Learning Distributed Representations of Code Changes—0
Investigating a Baseline Of Self Supervised Learning Towards Reducing Labeling Costs For Image Classification—0
Deep Learning Solutions for TanDEM-X-based Forest Classification—0
Inverting The Generator Of A Generative Adversarial Network—0
Inverted Semantic-Index for Image Retrieval—0
Deep Learning Reproducibility and Explainable AI (XAI)—0
Inverse-Free Fast Natural Gradient Descent Method for Deep Learning—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
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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