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 6851–6875 of 10420 papers

TitleStatusHype
Laconic Deep Learning Computing—0
Towards Non-I.I.D. Image Classification: A Dataset and Baselines—0
LABO: Towards Learning Optimal Label Regularization via Bi-level Optimization—0
Revisiting the Role of Label Smoothing in Enhanced Text Sentiment Classification—0
Label-similarity Curriculum Learning—0
Deep Residual Network based food recognition for enhanced Augmented Reality application—0
NN2CAM: Automated Neural Network Mapping for Multi-Precision Edge Processing on FPGA-Based Cameras—0
Label-noise-tolerant medical image classification via self-attention and self-supervised learning—0
Label Geometry Aware Discriminator for Conditional Generative Networks—0
Label Embedding with Partial Heterogeneous Contexts—0
Deep Residual Axial Networks—0
Noise-Contrastive Variational Information Bottleneck Networks—0
Label-Embedding for Attribute-Based Classification—0
Noise-reducing attention cross fusion learning transformer for histological image classification of osteosarcoma—0
Deep Repulsive Clustering of Ordered Data Based on Order-Identity Decomposition—0
Bayesian Optimization for Hyperparameters Tuning in Neural Networks—0
An Adaptive Sampling and Edge Detection Approach for Encoding Static Images for Spiking Neural Networks—0
NoisyAG-News: A Benchmark for Addressing Instance-Dependent Noise in Text Classification—0
Adaptive Region Pooling for Fine-Grained Representation Learning—0
Label-efficient Single Photon Images Classification via Active Learning—0
DeepRepair: Style-Guided Repairing for DNNs in the Real-world Operational Environment—0
Noisy Label Processing for Classification: A Survey—0
Label-Efficient Group Robustness via Out-of-Distribution Concept Curation—0
No more meta-parameter tuning in unsupervised sparse feature learning—0
Label Denoising through Cross-Model Agreement—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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified