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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 4701–4750 of 10420 papers

TitleStatusHype
Feature-EndoGaussian: Feature Distilled Gaussian Splatting in Surgical Deformable Scene Reconstruction—0
Feature Embedding by Template Matching as a ResNet Block—0
Comparison of Neural Models for X-ray Image Classification in COVID-19 Detection—0
Feature Density Estimation for Out-of-Distribution Detection via Normalizing Flows—0
Comparison of Methods Generalizing Max- and Average-Pooling—0
Feature Channel Adaptive Enhancement for Fine-Grained Visual Classification—0
Feature CAM: Interpretable AI in Image Classification—0
Comparison of fine-tuning strategies for transfer learning in medical image classification—0
Feature-based Graph Attention Networks Improve Online Continual Learning—0
Comparison of Batch Normalization and Weight Normalization Algorithms for the Large-scale Image Classification—0
Arithmetic Intensity Balancing Convolution for Hardware-aware Efficient Block Design—0
A Fast and Efficient Conditional Learning for Tunable Trade-Off between Accuracy and Robustness—0
A Convolutional Neural Network with Mapping Layers for Hyperspectral Image Classification—0
Feature Augmentation for Self-supervised Contrastive Learning: A Closer Look—0
Feature Alignment and Representation Transfer in Knowledge Distillation for Large Language Models—0
Feature Aligning Few shot Learning Method Using Local Descriptors Weighted Rules—0
Feature Activation Map: Visual Explanation of Deep Learning Models for Image Classification—0
Comparison Analysis of Traditional Machine Learning and Deep Learning Techniques for Data and Image Classification—0
Feasibility of Transfer Learning: A Mathematical Framework—0
Comparing LBP, HOG and Deep Features for Classification of Histopathology Images—0
Comparing concepts of quantum and classical neural network models for image classification task—0
FBNetV5: Neural Architecture Search for Multiple Tasks in One Run—0
Compare and Contrast: Learning Prominent Visual Differences—0
FAT: Training Neural Networks for Reliable Inference Under Hardware Faults—0
FATNN: Fast and Accurate Ternary Neural Networks—0
Comparator Networks—0
Arguments for the Unsuitability of Convolutional Neural Networks for Non--Local Tasks—0
A fast and Accurate Similarity-constrained Subspace Clustering Framework for Unsupervised Hyperspectral Image Classification—0
Comparative Study on Generative Adversarial Networks—0
Comparative study of variational quantum circuit and quantum backpropagation multilayer perceptron for COVID-19 outbreak predictions—0
argmax centroid—0
Fast-ParC: Capturing Position Aware Global Feature for ConvNets and ViTs—0
Comparative Investigation of Learning Algorithms for Image Classification with Small Dataset—0
Are Visual Recognition Models Robust to Image Compression?—0
Fast Parametric Learning with Activation Memorization—0
FAST OBJECT LOCALIZATION VIA SENSITIVITY ANALYSIS—0
Comparative Evaluation of Recent Universal Adversarial Perturbations in Image Classification—0
Are Vision Transformers Robust to Patch-wise Perturbations?—0
Fast Neural Architecture Construction using EnvelopeNets—0
Comparative Analysis of Multiple Deep CNN Models for Waste Classification—0
Fast Low-rank Representation based Spatial Pyramid Matching for Image Classification—0
Fast Image Scanning with Deep Max-Pooling Convolutional Neural Networks—0
Comparative Analysis of Lightweight Deep Learning Models for Memory-Constrained Devices—0
Are Vision Transformers Robust to Patch Perturbations?—0
Aerial Image Classification in Scarce and Unconstrained Environments via Conformal Prediction—0
Aerial Flood Scene Classification Using Fine-Tuned Attention-based Architecture for Flood-Prone Countries in South Asia—0
A convex method for classification of groups of examples—0
A baseline on continual learning methods for video action recognition—0
Fast Image Classification by Boosting Fuzzy Classifiers—0
Comparative Analysis of Imbalanced Malware Byteplot Image Classification using Transfer Learning—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