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

Showing 92269250 of 10420 papers

TitleStatusHype
Considerations for a PAP Smear Image Analysis System with CNN Features0
Pixel-level Reconstruction and Classification for Noisy Handwritten Bangla Characters0
A convex method for classification of groups of examples0
DPP-Net: Device-aware Progressive Search for Pareto-optimal Neural Architectures0
Finding Original Image Of A Sub Image Using CNNs0
Inference of Quantized Neural Networks on Heterogeneous All-Programmable Devices0
Maximally Invariant Data Perturbation as ExplanationCode0
RISE: Randomized Input Sampling for Explanation of Black-box ModelsCode1
Classification of remote sensing images using attribute profiles and feature profiles from different trees: a comparative study0
Recurrent Multiresolution Convolutional Networks for VHR Image Classification0
Non-Negative Networks Against Adversarial AttacksCode0
Image classification and retrieval with random depthwise signed convolutional neural networksCode0
Three dimensional Deep Learning approach for remote sensing image classification0
GLoMo: Unsupervisedly Learned Relational Graphs as Transferable RepresentationsCode0
Efficient Active Learning for Image Classification and Segmentation using a Sample Selection and Conditional Generative Adversarial Network0
NetScore: Towards Universal Metrics for Large-scale Performance Analysis of Deep Neural Networks for Practical On-Device Edge Usage0
Crowd-Powered Data Mining0
Manifold Mixup: Better Representations by Interpolating Hidden StatesCode1
Benchmarks for Image Classification and Other High-dimensional Pattern Recognition Problems0
Human Activity Recognition Based on Wearable Sensor Data: A Standardization of the State-of-the-ArtCode0
Knowledge Distillation by On-the-Fly Native EnsembleCode0
Bayesian Model-Agnostic Meta-LearningCode1
Improving Whole Slide Segmentation Through Visual Context - A Systematic Study0
Dual Pattern Learning Networks by Empirical Dual Prediction Risk Minimization0
A Systematic Evaluation of Recent Deep Learning Architectures for Fine-Grained Vehicle ClassificationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5DaViT-HTop 1 Accuracy90.2Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90Unverified