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 7751–7800 of 10420 papers

TitleStatusHype
A Very Compact Embedded CNN Processor Design Based on Logarithmic Computing—0
InceptionCapsule: Inception-Resnet and CapsuleNet with self-attention for medical image Classification—0
In Automation We Trust: Investigating the Role of Uncertainty in Active Learning Systems—0
A Main/Subsidiary Network Framework for Simplifying Binary Neural Networks—0
IMWA: Iterative Model Weight Averaging Benefits Class-Imbalanced Learning Tasks—0
Improving Whole Slide Segmentation Through Visual Context - A Systematic Study—0
RadTex: Learning Efficient Radiograph Representations from Text Reports—0
Deepfake Video Forensics based on Transfer Learning—0
Nonlinear Advantage: Trained Networks Might Not Be As Complex as You Think—0
RAID: Randomized Adversarial-Input Detection for Neural Networks—0
RAILS: A Robust Adversarial Immune-inspired Learning System—0
Improving Transferability of Deep Neural Networks—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
Adaptive Dataset Sampling by Deep Policy Gradient—0
Improving training of deep neural networks via Singular Value Bounding—0
A Study on Transformer Configuration and Training Objective—0
Deep Epitomic Convolutional Neural Networks—0
Improving the Reliability for Confidence Estimation—0
Randomized ICA and LDA Dimensionality Reduction Methods for Hyperspectral Image Classification—0
Randomized kernels for large scale Earth observation applications—0
Randomized Principal Component Analysis for Hyperspectral Image Classification—0
Random Laplace Feature Maps for Semigroup Kernels on Histograms—0
Random Padding Data Augmentation—0
Deep Ensembles for Low-Data Transfer Learning—0
A Machine-Synesthetic Approach To DDoS Network Attack Detection—0
Improving the Effectiveness of Deep Generative Data—0
Rank4Class: Examining Multiclass Classification through the Lens of Learning to Rank—0
Improving the Deployment of Recycling Classification through Efficient Hyper-Parameter Analysis—0
Rank Selection of CP-decomposed Convolutional Layers with Variational Bayesian Matrix Factorization—0
Deep Ensemble Bayesian Active Learning : Addressing the Mode Collapse issue in Monte Carlo dropout via Ensembles—0
Improving the accuracy of neural networks in analog computing-in-memory systems by a generalized quantization method—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
Improving the Accuracy of Learning Example Weights for Imbalance Classification—0
Improving Tail-Class Representation with Centroid Contrastive Learning—0
Improving Strong-Scaling of CNN Training by Exploiting Finer-Grained Parallelism—0
Improving STDP-based Visual Feature Learning with Whitening—0
Raw Waveform-based Audio Classification Using Sample-level CNN Architectures—0
RBFleX-NAS: Training-Free Neural Architecture Search Using Radial Basis Function Kernel and Hyperparameter Detection—0
RC-DARTS: Resource Constrained Differentiable Architecture Search—0
RCKD: Response-Based Cross-Task Knowledge Distillation for Pathological Image Analysis—0
DeepEMD: Few-Shot Image Classification With Differentiable Earth Mover's Distance and Structured Classifiers—0
R-Cut: Enhancing Explainability in Vision Transformers with Relationship Weighted Out and Cut—0
Auxiliary Multimodal LSTM for Audio-visual Speech Recognition and Lipreading—0
Reading Is Believing: Revisiting Language Bottleneck Models for Image Classification—0
Altogether: Image Captioning via Re-aligning Alt-text—0
Adaptive Data Augmentation with Deep Parallel Generative Models—0
Accurate and Efficient Similarity Search for Large Scale Face Recognition—0
Improving Feature Stability during Upsampling -- Spectral Artifacts and the Importance of Spatial Context—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