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 1551–1575 of 10420 papers

TitleStatusHype
A Method of Moments Embedding Constraint and its Application to Semi-Supervised LearningCode0
Implicit Generative Prior for Bayesian Neural NetworksCode0
SPLICE -- Streamlining Digital Pathology Image Processing—0
SDFD: Building a Versatile Synthetic Face Image Dataset with Diverse Attributes—0
Lacunarity Pooling Layers for Plant Image Classification using Texture AnalysisCode0
IMWA: Iterative Model Weight Averaging Benefits Class-Imbalanced Learning Tasks—0
MoDE: CLIP Data Experts via Clustering—0
Efficient Multi-Model Fusion with Adversarial Complementary Representation Learning—0
Brain Storm Optimization Based Swarm Learning for Diabetic Retinopathy Image Classification—0
MiMICRI: Towards Domain-centered Counterfactual Explanations of Cardiovascular Image Classification ModelsCode0
Rethinking model prototyping through the MedMNIST+ dataset collectionCode1
Vision Transformer-based Adversarial Domain AdaptationCode0
Compressed Meta-Optical Encoder for Image Classification—0
An MRP Formulation for Supervised Learning: Generalized Temporal Difference Learning Models—0
Deep multi-prototype capsule networks—0
Pyramid Hierarchical Transformer for Hyperspectral Image ClassificationCode1
A review of deep learning-based information fusion techniques for multimodal medical image classification—0
CoProNN: Concept-based Prototypical Nearest Neighbors for Explaining Vision ModelsCode1
Importance of Disjoint Sampling in Conventional and Transformer Models for Hyperspectral Image ClassificationCode0
A Comprehensive Survey for Hyperspectral Image Classification: The Evolution from Conventional to Transformers and Mamba ModelsCode1
Learning-to-learn enables rapid learning with phase-change memory-based in-memory computing—0
WangLab at MEDIQA-M3G 2024: Multimodal Medical Answer Generation using Large Language Models—0
CKD: Contrastive Knowledge Distillation from A Sample-wise PerspectiveCode0
EncodeNet: A Framework for Boosting DNN Accuracy with Entropy-driven Generalized Converting Autoencoder—0
I2CANSAY:Inter-Class Analogical Augmentation and Intra-Class Significance Analysis for Non-Exemplar Online Task-Free Continual 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
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