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

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Showing 2851–2900 of 10419 papers

TitleStatusHype
An Investigation on Hardware-Aware Vision Transformer Scaling—0
Advances in Hyperspectral Image Classification: Earth monitoring with statistical learning methods—0
An Introduction to Deep Visual Explanation—0
A Comparison for Anti-noise Robustness of Deep Learning Classification Methods on a Tiny Object Image Dataset: from Convolutional Neural Network to Visual Transformer and Performer—0
CapsuleRRT: Relationships-Aware Regression Tracking via Capsules—0
An Introduction to Deep Morphological Networks—0
3D Dense Separated Convolution Module for Volumetric Image Analysis—0
Enhancing CNN Classification with Lamarckian Memetic Algorithms and Local Search—0
Enhancing Counterfactual Image Generation Using Mahalanobis Distance with Distribution Preferences in Feature Space—0
Enhancing Glass Defect Detection with Diffusion Models: Addressing Imbalanced Datasets in Manufacturing Quality Control—0
Equivariance with Learned Canonicalization Functions—0
Advances in Deep Learning for Hyperspectral Image Analysis--Addressing Challenges Arising in Practical Imaging Scenarios—0
Capsule Network is Not More Robust than Convolutional Network—0
Enhanced Infield Agriculture with Interpretable Machine Learning Approaches for Crop Classification—0
An Interpretive Constrained Linear Model for ResNet and MgNet—0
Enhanced Image Classification With Data Augmentation Using Position Coordinates—0
Enhanced Object Detection via Fusion With Prior Beliefs from Image Classification—0
CapsNet comparative performance evaluation for image classification—0
CapsAttacks: Robust and Imperceptible Adversarial Attacks on Capsule Networks—0
An interpretation of the final fully connected layer—0
Can We Trust Explainable AI Methods on ASR? An Evaluation on Phoneme Recognition—0
A comparative study of semi- and self-supervised semantic segmentation of biomedical microscopy data—0
Enhanced Gradient for Differentiable Architecture Search—0
Enhanced Image Classification With a Fast-Learning Shallow Convolutional Neural Network—0
Can We Infer Confidential Properties of Training Data from LLMs?—0
Can weight sharing outperform random architecture search? An investigation with TuNAS—0
An Interactive Explanatory AI System for Industrial Quality Control—0
Can the state of relevant neurons in a deep neural networks serve as indicators for detecting adversarial attacks?—0
Can't Fool Me: Adversarially Robust Transformer for Video Understanding—0
An Intelligent Hybrid Model for Identity Document Classification—0
Can representation learning for multimodal image registration be improved by supervision of intermediate layers?—0
State Classification of Cooking Objects Using a VGG CNN—0
Canonical Correlation Analysis of Datasets with a Common Source Graph—0
GPT4Image: Can Large Pre-trained Models Help Vision Models on Perception Tasks?—0
Enhanced Attacks on Defensively Distilled Deep Neural Networks—0
Enhanced Prototypical Part Network (EPPNet) For Explainable Image Classification Via Prototypes—0
Can Language Models Use Forecasting Strategies?—0
Can KAN Work? Exploring the Potential of Kolmogorov-Arnold Networks in Computer Vision—0
Can Deep Neural Networks Match the Related Objects?: A Survey on ImageNet-trained Classification Models—0
Energy Efficient Hardware for On-Device CNN Inference via Transfer Learning—0
Cancer image classification based on DenseNet model—0
An In-depth Investigation of Sparse Rate Reduction in Transformer-like Models—0
Can a face tell us anything about an NBA prospect? -- A Deep Learning approach—0
A Comparative Study of Gastric Histopathology Sub-size Image Classification: from Linear Regression to Visual Transformer—0
A Comparative Study of Deep Learning Loss Functions for Multi-Label Remote Sensing Image Classification—0
Energy Efficient Hadamard Neural Networks—0
Energy-Efficient Model Compression and Splitting for Collaborative Inference Over Time-Varying Channels—0
Can a CNN Recognize Catalan Diet?—0
A Dot Product Attention Free Transformer—0
Camera Bias in a Fine Grained Classification Task—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