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 5901–5925 of 10420 papers

TitleStatusHype
How Out-of-Distribution Detection Learning Theory Enhances Transformer: Learnability and Reliability—0
Coverage Testing of Deep Learning Models using Dataset Characterization—0
MBInception: A new Multi-Block Inception Model for Enhancing Image Processing Efficiency—0
flexgrid2vec: Learning Efficient Visual Representations Vectors—0
A Hybrid Differential Evolution Approach to Designing Deep Convolutional Neural Networks for Image Classification—0
Let's Go Shopping (LGS) -- Web-Scale Image-Text Dataset for Visual Concept Understanding—0
Covariance-corrected Whitening Alleviates Network Degeneration on Imbalanced Classification—0
G-RepsNet: A Fast and General Construction of Equivariant Networks for Arbitrary Matrix Groups—0
Coupling Visual Semantics of Artificial Neural Networks and Human Brain Function via Synchronized Activations—0
Leveraging Chat-Based Large Vision Language Models for Multimodal Out-Of-Context Detection—0
Active Transfer Learning with Zero-Shot Priors: Reusing Past Datasets for Future Tasks—0
Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation—0
GreedyNAS: Towards Fast One-Shot NAS with Greedy Supernet—0
Leveraging Conditional Mutual Information to Improve Large Language Model Fine-Tuning For Classification—0
Leveraging counterfactual concepts for debugging and improving CNN model performance—0
Maxmin convolutional neural networks for image classification—0
Leveraging Deep Learning and Xception Architecture for High-Accuracy MRI Classification in Alzheimer Diagnosis—0
Leveraging Diffusion Models for Synthetic Data Augmentation in Protein Subcellular Localization Classification—0
MaxUp: Lightweight Adversarial Training With Data Augmentation Improves Neural Network Training—0
MCFNet: A Multimodal Collaborative Fusion Network for Fine-Grained Semantic Classification—0
Diagnosis of Alzheimer's Disease via Multi-modality 3D Convolutional Neural Network—0
Leveraging Internal Representations of Model for Magnetic Image Classification—0
Maximal Independent Vertex Set applied to Graph Pooling—0
Multimodal Adversarial Defense for Vision-Language Models by Leveraging One-To-Many Relationships—0
Attack Agnostic Statistical Method for Adversarial Detection—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