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 3201–3225 of 10420 papers

TitleStatusHype
Domain Aligned CLIP for Few-shot Classification—0
Domain-decomposed image classification algorithms using linear discriminant analysis and convolutional neural networks—0
Direct Image Classification from Fourier Ptychographic Microscopy Measurements without Reconstruction—0
What Do Single-view 3D Reconstruction Networks Learn?—0
Building Human-like Communicative Intelligence: A Grounded Perspective—0
Detached Error Feedback for Distributed SGD with Random Sparsification—0
Explore the Power of Dropout on Few-shot Learning—0
ADINet: Attribute Driven Incremental Network for Retinal Image Classification—0
Domain-Invariant Disentangled Network for Generalizable Object Detection—0
Buildings Detection in VHR SAR Images Using Fully Convolution Neural Networks—0
Exploring Deep Learning Methods for Classification of SAR Images: Towards NextGen Convolutions via Transformers—0
Domain Wall Magnetic Tunnel Junction Reliable Integrate and Fire Neuron—0
Do More Dropouts in Pool5 Feature Maps for Better Object Detection—0
Bundle Optimization for Multi-aspect Embedding—0
DiRaC-I: Identifying Diverse and Rare Training Classes for Zero-Shot Learning—0
Blackbox Trojanising of Deep Learning Models : Using non-intrusive network structure and binary alterations—0
A Compact Representation of Histopathology Images using Digital Stain Separation & Frequency-Based Encoded Local Projections—0
Don’t Wait, Just Weight: Improving Unsupervised Representations by Learning Goal-Driven Instance Weights—0
DINO-CXR: A self supervised method based on vision transformer for chest X-ray classification—0
Dopamine Transporter SPECT Image Classification for Neurodegenerative Parkinsonism via Diffusion Maps and Machine Learning Classifiers—0
Faster Adaptive Federated Learning—0
Black Box to White Box: Discover Model Characteristics Based on Strategic Probing—0
Do the Frankenstein, or how to achieve better out-of-distribution performance with manifold mixing model soup—0
Double-Stage Feature-Level Clustering-Based Mixture of Experts Framework—0
An efficient and flexible inference system for serving heterogeneous ensembles of deep neural networks—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