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 4501–4525 of 10420 papers

TitleStatusHype
A Main/Subsidiary Network Framework for Simplifying Binary Neural Networks—0
Image Classification using Fuzzy Pooling in Convolutional Kolmogorov-Arnold Networks—0
Nonlinear Advantage: Trained Networks Might Not Be As Complex as You Think—0
Deepfake Video Forensics based on Transfer Learning—0
Adaptive Dataset Sampling by Deep Policy Gradient—0
Deep Expectation of Real and Apparent Age from a Single Image Without Facial Landmarks—0
A Main/Subsidiary Network Framework for Simplifying Binary Neural Network—0
Image Classification using Combination of Topological Features and Neural Networks—0
Image Classification using Graph Neural Network and Multiscale Wavelet Superpixels—0
A Study on Transformer Configuration and Training Objective—0
Deep Epitomic Convolutional Neural Networks—0
Altogether: Image Captioning via Re-aligning Alt-text—0
A Machine-Synesthetic Approach To DDoS Network Attack Detection—0
Deep Ensembles for Low-Data Transfer Learning—0
Adaptive Data Augmentation with Deep Parallel Generative Models—0
Image Classification Using a Diffusion Model as a Pre-Training Model—0
Deep Ensemble Bayesian Active Learning : Addressing the Mode Collapse issue in Monte Carlo dropout via Ensembles—0
Deep Ensemble Bayesian Active Learning : Adressing the Mode Collapse issue in Monte Carlo dropout via Ensembles—0
Auxiliary Tasks Enhanced Dual-affinity Learning for Weakly Supervised Semantic Segmentation—0
DeepEMD: Few-Shot Image Classification With Differentiable Earth Mover's Distance and Structured Classifiers—0
Auxiliary Multimodal LSTM for Audio-visual Speech Recognition and Lipreading—0
Image Classification using CNN for Traffic Signs in Pakistan—0
Image classification using local tensor singular value decompositions—0
Image Classification with Rejection using Contextual Information—0
Deep Elastic Networks with Model Selection for Multi-Task 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