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 2901–2950 of 10419 papers

TitleStatusHype
Camera Bias in a Fine Grained Classification Task—0
Enhancing Whole Slide Image Classification through Supervised Contrastive Domain Adaptation—0
An Improved CNN-based Neural Network Model for Fruit Sugar Level Detection—0
An image segmentation algorithm for measurement of flotation froth bubble size distributions—0
Enhancing Transformers Through Conditioned Embedded Tokens—0
Enrich the content of the image Using Context-Aware Copy Paste—0
Ensemble of Part Detectors for Simultaneous Classification and Localization—0
A Comparative Study of Confidence Calibration in Deep Learning: From Computer Vision to Medical Imaging—0
Boldness-Recalibration for Binary Event Predictions—0
Enhancing Small Object Encoding in Deep Neural Networks: Introducing Fast&Focused-Net with Volume-wise Dot Product Layer—0
Calibrating Histopathology Image Classifiers using Label Smoothing—0
Calibrating Deep Neural Networks using Explicit Regularisation and Dynamic Data Pruning—0
Enhancing the Convergence of Federated Learning Aggregation Strategies with Limited Data—0
Enhancing ResNet Image Classification Performance by using Parameterized Hypercomplex Multiplication—0
A Domain Decomposition-Based CNN-DNN Architecture for Model Parallel Training Applied to Image Recognition Problems—0
Enhancing Robustness of Machine Learning Systems via Data Transformations—0
An Extendable, Efficient and Effective Transformer-based Object Detector—0
CAIPI in Practice: Towards Explainable Interactive Medical Image Classification—0
A Comparative Study of CNN, BoVW and LBP for Classification of Histopathological Images—0
Enhancing the Performance of Convolutional Neural Networks on Quality Degraded Datasets—0
CageViT: Convolutional Activation Guided Efficient Vision Transformer—0
CADICA: a new dataset for coronary artery disease detection by using invasive coronary angiography—0
An Experimental Study of Reduced-Voltage Operation in Modern FPGAs for Neural Network Acceleration—0
CacheNet: A Model Caching Framework for Deep Learning Inference on the Edge—0
Admissibility of Stein Shrinkage for Batch Normalization in the Presence of Adversarial Attacks—0
A Distributed Deep Representation Learning Model for Big Image Data Classification—0
C2S2: Cost-aware Channel Sparse Selection for Progressive Network Pruning—0
C2G-Net: Exploiting Morphological Properties for Image Classification—0
A New Window Loss Function for Bone Fracture Detection and Localization in X-ray Images with Point-based Annotation—0
Enhancing Representations through Heterogeneous Self-Supervised Learning—0
Enhancing the Regularization Effect of Weight Pruning in Artificial Neural Networks—0
C2AE: Class Conditioned Auto-Encoder for Open-set Recognition—0
A New Perspective to Boost Vision Transformer for Medical Image Classification—0
Enhancing Neural Training via a Correlated Dynamics Model—0
Byzantines can also Learn from History: Fall of Centered Clipping in Federated Learning—0
Byzantine-Robust and Communication-Efficient Distributed Learning via Compressed Momentum Filtering—0
3DSS-Mamba: 3D-Spectral-Spatial Mamba for Hyperspectral Image Classification—0
Enhancing One-run Privacy Auditing with Quantile Regression-Based Membership Inference—0
Enhancing JEPAs with Spatial Conditioning: Robust and Efficient Representation Learning—0
Bytes Are All You Need: Transformers Operating Directly On File Bytes—0
Enhancing Layer Attention Efficiency through Pruning Redundant Retrievals—0
A Compact Representation of Histopathology Images using Digital Stain Separation & Frequency-Based Encoded Local Projections—0
BUZz: BUffer Zones for defending adversarial examples in image classification—0
Enhancing Intrinsic Features for Debiasing via Investigating Class-Discerning Common Attributes in Bias-Contrastive Pair—0
Enhancing Multimodal In-Context Learning for Image Classification through Coreset Optimization—0
Enhancing Performance of Vision Transformers on Small Datasets through Local Inductive Bias Incorporation—0
Bundle Optimization for Multi-aspect Embedding—0
Building Vision Transformers with Hierarchy Aware Feature Aggregation—0
A New Ensemble Method for Concessively Targeted Multi-model Attack—0
Buildings Detection in VHR SAR Images Using Fully Convolution Neural Networks—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