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 7151–7200 of 10420 papers

TitleStatusHype
Unsupervised Continual Learning Via Pseudo Labels—0
Fully Connected Deep Structured Networks—0
Abnormal Client Behavior Detection in Federated Learning—0
Classification for everyone : Building geography agnostic models for fairer recognition—0
Open Vocabulary Multi-Label Video Classification—0
Full-attention based Neural Architecture Search using Context Auto-regression—0
A Study of Compositional Generalization in Neural Models—0
Anticipating Future Object Compositions without Forgetting—0
Dual-Activated Lightweight Attention ResNet50 for Automatic Histopathology Breast Cancer Image Classification—0
PCGAN-CHAR: Progressively Trained Classifier Generative Adversarial Networks for Classification of Noisy Handwritten Bangla Characters—0
Peak Detection On Data Independent Acquisition Mass Spectrometry Data With Semisupervised Convolutional Transformers—0
Perception Improvement for Free: Exploring Imperceptible Black-box Adversarial Attacks on Image Classification—0
Operator-learning-inspired Modeling of Neural Ordinary Differential Equations—0
Optical Neural Networks—0
Optical Neural Ordinary Differential Equations—0
Optical Remote Sensing Image Understanding with Weak Supervision: Concepts, Methods, and Perspectives—0
FSNet: Compression of Deep Convolutional Neural Networks by Filter Summary—0
Continual Learning for Class- and Domain-Incremental Semantic Segmentation—0
Optimal Control for Transformer Architectures: Enhancing Generalization, Robustness and Efficiency—0
Optimal Layer Selection for Latent Data Augmentation—0
Fruit-HSNet: A Machine Learning Approach for Hyperspectral Image-Based Fruit Ripeness Prediction—0
Optimal Smoothing Distribution Exploration for Backdoor Neutralization in Deep Learning-based Traffic Systems—0
Continual learning benefits from multiple sleep mechanisms: NREM, REM, and Synaptic Downscaling—0
A Study of BFLOAT16 for Deep Learning Training—0
Frugal Reinforcement-based Active Learning—0
Optimization of Autonomous Driving Image Detection Based on RFAConv and Triplet Attention—0
Optimization on Submanifolds of Convolution Kernels in CNNs—0
Automatic Design of CNNs via Differentiable Neural Architecture Search for PolSAR Image Classification—0
Optimized Generic Feature Learning for Few-shot Classification across Domains—0
Optimized Learning for X-Ray Image Classification for Multi-Class Disease Diagnoses with Accelerated Computing Strategies—0
Optimized Tradeoffs for Private Prediction with Majority Ensembling—0
Optimizing Breast Cancer Detection in Mammograms: A Comprehensive Study of Transfer Learning, Resolution Reduction, and Multi-View Classification—0
Efficient Online ML API Selection for Multi-Label Classification Tasks—0
Optimizing Convolutional Neural Networks for Embedded Systems by Means of Neuroevolution—0
Enhancing Glass Defect Detection with Diffusion Models: Addressing Imbalanced Datasets in Manufacturing Quality Control—0
Optimizing Deep Learning Inference on Embedded Systems Through Adaptive Model Selection—0
Optimizing Estimators of Squared Calibration Errors in Classification—0
Optimizing Explanations by Network Canonization and Hyperparameter Search—0
Optimizing Federated Learning for Medical Image Classification on Distributed Non-iid Datasets with Partial Labels—0
Optimizing Gastrointestinal Diagnostics: A CNN-Based Model for VCE Image Classification—0
Frozen Feature Augmentation for Few-Shot Image Classification—0
Optimizing Multi-Domain Performance with Active Learning-based Improvement Strategies—0
Optimizing Neural Network Performance and Interpretability with Diophantine Equation Encoding—0
Enhancing Intrinsic Features for Debiasing via Investigating Class-Discerning Common Attributes in Bias-Contrastive Pair—0
Frost filtered scale-invariant feature extraction and multilayer perceptron for hyperspectral image classification—0
Optimizing speed/accuracy trade-off for person re-identification via knowledge distillation—0
Oral squamous cell detection using deep learning—0
Enhancing Layer Attention Efficiency through Pruning Redundant Retrievals—0
Orchid: Flexible and Data-Dependent Convolution for Sequence Modeling—0
A Study for Universal Adversarial Attacks on Texture Recognition—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