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 3601–3650 of 10420 papers

TitleStatusHype
Enhancing Neural Training via a Correlated Dynamics Model—0
Enhancing One-run Privacy Auditing with Quantile Regression-Based Membership Inference—0
Flip-Rotate-Pooling Convolution and Split Dropout on Convolution Neural Networks for Image Classification—0
Enhancing Post-Hoc Explanation Benchmark Reliability for Image Classification—0
Enhancing Representations through Heterogeneous Self-Supervised Learning—0
Enhancing ResNet Image Classification Performance by using Parameterized Hypercomplex Multiplication—0
Development of CNN Architectures using Transfer Learning Methods for Medical Image Classification—0
An Artificial Neural Network for Image Classification Inspired by Aversive Olfactory Learning Circuits in Caenorhabditis Elegans—0
Enhancing Small Object Encoding in Deep Neural Networks: Introducing Fast&Focused-Net with Volume-wise Dot Product Layer—0
Enhancing the Convergence of Federated Learning Aggregation Strategies with Limited Data—0
Enhancing the Performance of Convolutional Neural Networks on Quality Degraded Datasets—0
Enhancing the Regularization Effect of Weight Pruning in Artificial Neural Networks—0
Enhancing Transfer Learning for Medical Image Classification with SMOTE: A Comparative Study—0
Enhancing Transformers Through Conditioned Embedded Tokens—0
Development Of A Fire Detection System On Satellite Images—0
Enhancing Whole Slide Image Classification through Supervised Contrastive Domain Adaptation—0
Enrich the content of the image Using Context-Aware Copy Paste—0
Classifying and Segmenting Microscopy Images Using Convolutional Multiple Instance Learning—0
Ensemble learning of diffractive optical networks—0
Ensemble of CNN classifiers using Sugeno Fuzzy Integral Technique for Cervical Cytology Image Classification—0
Classifying Images with CoLaNET Spiking Neural Network -- the MNIST Example—0
Ensemble of Models Trained by Key-based Transformed Images for Adversarially Robust Defense Against Black-box Attacks—0
FLOAT: FAST LEARNABLE ONCE-FOR-ALL ADVERSARIAL TRAINING FOR TUNABLE TRADE-OFF BETWEEN ACCURACY AND ROBUSTNESS—0
Ensembles of feedforward-designed convolutional neural networks—0
Ensemble Soft-Margin Softmax Loss for Image Classification—0
Classifying neuromorphic data using a deep learning framework for image classification—0
Developing Convolutional Neural Networks using a Novel Lamarckian Co-Evolutionary Algorithm—0
Developing a Recommendation Benchmark for MLPerf Training and Inference—0
Entanglement and Tensor Networks for Supervised Image Classification—0
Entanglement Entropy of Target Functions for Image Classification and Convolutional Neural Network—0
DetNet: Design Backbone for Object Detection—0
Entrenamiento de una red neuronal para el reconocimiento de imagenes de lengua de senas capturadas con sensores de profundidad—0
Bias mitigation techniques in image classification: fair machine learning in human heritage collections—0
A Closed-Form Learned Pooling for Deep Classification Networks—0
An approach based on class activation maps for investigating the effects of data augmentation on neural networks for image classification—0
Entropy-Driven Mixed-Precision Quantization for Deep Network Design—0
Entropy Induced Pruning Framework for Convolutional Neural Networks—0
Class-incremental learning: survey and performance evaluation on image classification—0
2nd Place Solution for ICCV 2021 VIPriors Image Classification Challenge: An Attract-and-Repulse Learning Approach—0
Flat-LoRA: Low-Rank Adaption over a Flat Loss Landscape—0
Class Incremental Learning with Task-Specific Batch Normalization and Out-of-Distribution Detection—0
Flatten: Video Action Recognition is an Image Classification task—0
Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models—0
Detection of Plant Leaf Disease Directly in the JPEG Compressed Domain using Transfer Learning Technique—0
Class Instance Balanced Learning for Long-Tailed Classification—0
Equivariance with Learned Canonicalization Functions—0
Detection of Non-uniformity in Parameters for Magnetic Domain Pattern Generation by Machine Learning—0
Bias-Eliminating Augmentation Learning for Debiased Federated Learning—0
Equivariant Neural Tangent Kernels—0
Detection of Degraded Acacia tree species using deep neural networks on uav drone imagery—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
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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