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 6151–6200 of 10420 papers

TitleStatusHype
Cost-efficient segmentation of electron microscopy images using active learning—0
Gradient Weighted Superpixels for Interpretability in CNNs—0
Atmospheric Noise-Resilient Image Classification in a Real-World Scenario: Using Hybrid CNN and Pin-GTSVM—0
Active Multi-Kernel Domain Adaptation for Hyperspectral Image Classification—0
Masked Face Image Classification with Sparse Representation based on Majority Voting Mechanism—0
Gradient Scaling on Deep Spiking Neural Networks with Spike-Dependent Local Information—0
CosSGD: Communication-Efficient Federated Learning with a Simple Cosine-Based Quantization—0
Gradient Obfuscation Gives a False Sense of Security in Federated Learning—0
Gradient Normalization & Depth Based Decay For Deep Learning—0
Masked Reconstruction Contrastive Learning with Information Bottleneck Principle—0
A Hierarchical Fused Quantum Fuzzy Neural Network for Image Classification—0
ExPLoit: Extracting Private Labels in Split Learning—0
A Theory of PAC Learnability under Transformation Invariances—0
Gradient-EM Bayesian Meta-learning—0
Disentangling Visual Transformers: Patch-level Interpretability for Image Classification—0
Cortical microcircuits as gated-recurrent neural networks—0
A Hierarchical Deep Convolutional Neural Network and Gated Recurrent Unit Framework for Structural Damage Detection—0
Disguised-Nets: Image Disguising for Privacy-preserving Outsourced Deep Learning—0
Matching Distributions via Optimal Transport for Semi-Supervised Learning—0
Matching Feature Sets for Few-Shot Image Classification—0
Gradient-based Wang-Landau Algorithm: A Novel Sampler for Output Distribution of Neural Networks over the Input Space—0
Corrupted Image Modeling for Self-Supervised Visual Pre-Training—0
Disrupting Model Training with Adversarial Shortcuts—0
Matrix Is All You Need—0
Gradient-based Class Weighting for Unsupervised Domain Adaptation in Dense Prediction Visual Tasks—0
Corrosion Detection for Industrial Objects: From Multi-Sensor System to 5D Feature Space—0
A Text-Image Pair Is not Enough: Language-Vision Relation Inference with Auxiliary Modality Translation—0
Model-Agnostic Learning to Meta-Learn—0
Model-Agnostic Meta-Learning for Multimodal Task Distributions—0
Maximal Independent Vertex Set applied to Graph Pooling—0
Modeling Collaborator: Enabling Subjective Vision Classification With Minimal Human Effort via LLM Tool-Use—0
An empirical study of the relation between network architecture and complexity—0
Adaptive Gradient Clipping for Robust Federated Learning—0
Maximum Categorical Cross Entropy (MCCE): A noise-robust alternative loss function to mitigate racial bias in Convolutional Neural Networks (CNNs) by reducing overfitting—0
Understanding Dropout as an Optimization Trick—0
Maximum Entropy Regularization and Chinese Text Recognition—0
Correlative and Discriminative Label Grouping for Multi-Label Visual Prompt Tuning—0
Maxmin convolutional neural networks for image classification—0
GQKVA: Efficient Pre-training of Transformers by Grouping Queries, Keys, and Values—0
A Technical Report for VIPriors Image Classification Challenge—0
MoCo-Pretraining Improves Representations and Transferability of Chest X-ray Models—0
MaxUp: Lightweight Adversarial Training With Data Augmentation Improves Neural Network Training—0
GPT-4 Vision on Medical Image Classification -- A Case Study on COVID-19 Dataset—0
Mayfly optimization with deep learning enabled retinal fundus image classification model—0
GPT4MIA: Utilizing Generative Pre-trained Transformer (GPT-3) as A Plug-and-Play Transductive Model for Medical Image Analysis—0
MBInception: A new Multi-Block Inception Model for Enhancing Image Processing Efficiency—0
A Deep Bayesian Convolutional Spiking Neural Network-based CAD system with Uncertainty Quantification for Medical Images Classification—0
MCFNet: A Multimodal Collaborative Fusion Network for Fine-Grained Semantic Classification—0
A Hierarchical Conditional Random Field-based Attention Mechanism Approach for Gastric Histopathology Image Classification—0
GP-NAS: Gaussian Process Based Neural Architecture Search—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