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 7001–7050 of 10420 papers

TitleStatusHype
Knowledge Distillation for Incremental Learning in Semantic Segmentation—0
Knowledge Concentration: Learning 100K Object Classifiers in a Single CNN—0
Knowledge-Aware Prompt Tuning for Generalizable Vision-Language Models—0
One-Shot Online Testing of Deep Neural Networks Based on Distribution Shift Detection—0
Knowledge accumulating: The general pattern of learning—0
One Size Does Not Fit All: Quantifying and Exposing the Accuracy-Latency Trade-off in Machine Learning Cloud Service APIs via Tolerance Tiers—0
Deep Octonion Networks—0
Adaptive Noise-Tolerant Network for Image Segmentation—0
Knee or ROC—0
One-Vote Veto: Semi-Supervised Learning for Low-Shot Glaucoma Diagnosis—0
DeepObfuscator: Obfuscating Intermediate Representations with Privacy-Preserving Adversarial Learning on Smartphones—0
K for the Price of 1: Parameter-efficient Multi-task and Transfer Learning—0
On Expected Accuracy—0
On Expert Estimation in Hierarchical Mixture of Experts: Beyond Softmax Gating Functions—0
KeystoneML: Optimizing Pipelines for Large-Scale Advanced Analytics—0
Deep Nonparametric Convexified Filtering for Computational Photography, Image Synthesis and Adversarial Defense—0
Bayesian Adaptation for Covariate Shift—0
On fine-tuning of Autoencoders for Fuzzy rule classifiers—0
Key Design Choices in Source-Free Unsupervised Domain Adaptation: An In-depth Empirical Analysis—0
Kernel Task-Driven Dictionary Learning for Hyperspectral Image Classification—0
On Generalization and Regularization in Deep Learning—0
DeepN-JPEG: A Deep Neural Network Favorable JPEG-based Image Compression Framework—0
Kernel Reconstruction ICA for Sparse Representation—0
Kernel principal component analysis network for image classification—0
Deep Neural Networks With Region-Based Pooling Structures for Mammographic Image Classification—0
On Learning the Structure of Clusters in Graphs—0
On Leave-One-Out Conditional Mutual Information For Generalization—0
Online Algorithms for Hierarchical Inference in Deep Learning applications at the Edge—0
Kernel Methods on Approximate Infinite-Dimensional Covariance Operators for Image Classification—0
Kernel Methods in Hyperbolic Spaces—0
Kernelized Support Tensor Train Machines—0
Deep Neural Networks Learn Meta-Structures from Noisy Labels in Semantic Segmentation—0
Baybayin Character Instance Detection—0
A Multi-Scale Isolation Forest Approach for Real-Time Detection and Filtering of FGSM Adversarial Attacks in Video Streams of Autonomous Vehicles—0
Achieving Explainability for Plant Disease Classification with Disentangled Variational Autoencoders—0
To Store or Not? Online Data Selection for Federated Learning with Limited Storage—0
Kernel Inversed Pyramidal Resizing Network for Efficient Pavement Distress Recognition—0
Online Feature Selection with Group Structure Analysis—0
Deep Neural Networks Fused with Textures for Image Classification—0
Kernel Extreme Learning Machine Optimized by the Sparrow Search Algorithm for Hyperspectral Image Classification—0
Deep Neural Networks for Pattern Recognition—0
Online Learning to Sample—0
Kernel Descriptors for Visual Recognition—0
Deep Neural Networks for Object Detection—0
KerCNNs: biologically inspired lateral connections for classification of corrupted images—0
Deep Neural Networks for Marine Debris Detection in Sonar Images—0
Batch Normalization: Accelerating Deep Network Training byReducing Internal Covariate Shift—0
A Multi-resolution Model for Histopathology Image Classification and Localization with Multiple Instance Learning—0
Keep your distance: learning dispersed embeddings on S_m—0
Keep Your AI-es on the Road: Tackling Distracted Driver Detection with Convolutional Neural Networks and Targeted Data Augmentation—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