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 5101–5125 of 10420 papers

TitleStatusHype
CSA: Data-efficient Mapping of Unimodal Features to Multimodal Features—0
Deep Axial Hypercomplex Networks—0
Histopathology Image Classification using Deep Manifold Contrastive Learning—0
Attribute Mix: Semantic Data Augmentation for Fine Grained Recognition—0
Knee or ROC—0
Deep Boosting: Joint Feature Selection and Analysis Dictionary Learning in Hierarchy—0
KO: Kinetics-inspired Neural Optimizer with PDE Simulation Approaches—0
Improving Bag-of-Visual-Words Towards Effective Facial Expressive Image Classification—0
ALoRE: Efficient Visual Adaptation via Aggregating Low Rank Experts—0
Improving Chest X-Ray Classification by RNN-based Patient Monitoring—0
Airway Label Prediction in Video Bronchoscopy: Capturing Temporal Dependencies Utilizing Anatomical Knowledge—0
Improving CNN classifiers by estimating test-time priors—0
Cryo-Electron Microscopy Image Analysis Using Multi-Frequency Vector Diffusion Maps—0
Kernel Methods on Approximate Infinite-Dimensional Covariance Operators for Image Classification—0
Histopathological Image Classification and Vulnerability Analysis using Federated Learning—0
Improving Deep Learning through Automatic Programming—0
Deep CNNs for large scale species classification—0
Improving Deep Neural Networks with Probabilistic Maxout Units—0
Histograms of Pattern Sets for Image Classification and Object Recognition—0
Crowdsourcing with Meta-Workers: A New Way to Save the Budget—0
Kernel principal component analysis network for image classification—0
Improving Explainability of Image Classification in Scenarios with Class Overlap: Application to COVID-19 and Pneumonia—0
Deep Collaborative Learning for Visual Recognition—0
Improving Few-Shot Image Classification Using Machine- and User-Generated Natural Language Descriptions—0
Crowd-Powered Data Mining—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