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 6951–7000 of 10420 papers

TitleStatusHype
OpenMixup: Open Mixup Toolbox and Benchmark for Visual Representation Learning—0
Contraction Mapping of Feature Norms for Classifier Learning on the Data with Different Quality—0
A Surrogate-Assisted Highly Cooperative Coevolutionary Algorithm for Hyperparameter Optimization in Deep Convolutional Neural Network—0
ODSmoothGrad: Generating Saliency Maps for Object Detectors—0
Galaxy Classification Using Transfer Learning and Ensemble of CNNs With Multiple Colour Spaces—0
Offloading Algorithms for Maximizing Inference Accuracy on Edge Device Under a Time Constraint—0
ContraCluster: Learning to Classify without Labels by Contrastive Self-Supervision and Prototype-Based Semi-Supervision—0
Efficient Sparse Artificial Neural Networks—0
OLID I: an open leaf image dataset for plant stress recognition—0
OmniVec2 - A Novel Transformer based Network for Large Scale Multimodal and Multitask Learning—0
GAF-NAU: Gramian Angular Field encoded Neighborhood Attention U-Net for Pixel-Wise Hyperspectral Image Classification—0
OmniVL:One Foundation Model for Image-Language and Video-Language Tasks—0
A Supervised STDP-based Training Algorithm for Living Neural Networks—0
Open-Set: ID Card Presentation Attack Detection using Neural Transfer Style—0
Open Vocabulary Multi-Label Video Classification—0
On Benefits of Selection Diversity via Bilevel Exclusive Sparsity—0
On-board classification of underwater images using hybrid classical-quantum CNN based method—0
Chest X-ray Image Classification: A Causal Perspective—0
Optical Neural Ordinary Differential Equations—0
ORXE: Orchestrating Experts for Dynamically Configurable Efficiency—0
On-Chip Learning with Memristor-Based Neural Networks: Assessing Accuracy and Efficiency Under Device Variations, Conductance Errors, and Input Noise—0
PARIC: Probabilistic Attention Regularization for Language Guided Image Classification from Pre-trained Vison Language Models—0
G2NetPL: Generic Game-Theoretic Network for Partial-Label Image Classification—0
On Connections between Regularizations for Improving DNN Robustness—0
FV-MgNet: Fully Connected V-cycle MgNet for Interpretable Time Series Forecasting—0
Continuous-Time Meta-Learning with Forward Mode Differentiation—0
Chest X-rays Classification: A Multi-Label and Fine-Grained Problem—0
OnDev-LCT: On-Device Lightweight Convolutional Transformers towards federated learning—0
Fuzzy Rank-based Late Fusion Technique for Cytology image Segmentation—0
On Direct Distribution Matching for Adapting Segmentation Networks—0
ELA: Efficient Local Attention for Deep Convolutional Neural Networks—0
One-bit Supervision for Image Classification: Problem, Solution, and Beyond—0
A Supervised Segmentation Network for Hyperspectral Image Classification—0
A General Upper Bound for Unsupervised Domain Adaptation—0
One-D-Piece: Image Tokenizer Meets Quality-Controllable Compression—0
On effects of Knowledge Distillation on Transfer Learning—0
Fuzzy Pooling—0
Fuzzy Pooling—0
Continuous Convolutional Neural Networks for Image Classification—0
Fuzzy-Based Dialectical Non-Supervised Image Classification and Clustering—0
Fuzzy-aware Loss for Source-free Domain Adaptation in Visual Emotion Recognition—0
Continual Learning with Transformers for Image Classification—0
A Supervised Neural Autoregressive Topic Model for Simultaneous Image Classification and Annotation—0
On Using Transfer Learning For Plant Disease Detection—0
ASU-CNN: An Efficient Deep Architecture for Image Classification and Feature Visualizations—0
Fusion of Foundation and Vision Transformer Model Features for Dermatoscopic Image Classification—0
One-Shot Adaptation of Supervised Deep Convolutional Models—0
Elucidating and Overcoming the Challenges of Label Noise in Supervised Contrastive Learning—0
A study on the Interpretability of Neural Retrieval Models using DeepSHAP—0
Fusion of evidential CNN classifiers for image classification—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