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

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Showing 6401–6450 of 10420 papers

TitleStatusHype
Vision Transformers For Weeds and Crops Classification Of High Resolution UAV Images—0
Cross-token Modeling with Conditional Computation—0
Real-World Adversarial Examples involving Makeup Application—0
ISyNet: Convolutional Neural Networks design for AI acceleratorCode0
CAM-loss: Towards Learning Spatially Discriminative Feature Representations—0
Access Control Using Spatially Invariant Permutation of Feature Maps for Semantic Segmentation Models—0
Ghost Loss to Question the Reliability of Training Data—0
Transfer of Pretrained Model Weights Substantially Improves Semi-Supervised Image ClassificationCode0
Better Self-training for Image Classification through Self-supervisionCode0
Impact of Attention on Adversarial Robustness of Image Classification Models—0
Cross-Model Consensus of Explanations and Beyond for Image Classification Models: An Empirical Study—0
The Impact of Reinitialization on Generalization in Convolutional Neural Networks—0
Multilingual Image Corpus: Annotation Protocol—0
EG-Booster: Explanation-Guided Booster of ML Evasion AttacksCode0
Spike time displacement based error backpropagation in convolutional spiking neural networks—0
PACE: Posthoc Architecture-Agnostic Concept Extractor for Explaining CNNs—0
Deep Generative Modeling for Protein Design—0
Quantized Convolutional Neural Networks Through the Lens of Partial Differential Equations—0
AIP: Adversarial Iterative Pruning Based on Knowledge Transfer for Convolutional Neural Networks—0
Communication-Computation Efficient Device-Edge Co-Inference via AutoML—0
Object-aware Long-short-range Spatial Alignment for Few-Shot Fine-Grained Image Classification—0
Privacy-preserving Machine Learning for Medical Image Classification—0
Representation Memorization for Fast Learning New Knowledge without Forgetting—0
Goal-driven text descriptions for images—0
New Pruning Method Based on DenseNet Network for Image Classification—0
ChessMix: Spatial Context Data Augmentation for Remote Sensing Semantic SegmentationCode0
A Comparison of Deep Saliency Map Generators on Multispectral Data in Object Detection—0
LocTex: Learning Data-Efficient Visual Representations from Localized Textual Supervision—0
An Automatic Image Content Retrieval Method for better Mobile Device Display User Experiences—0
Robust Long-Tailed Learning under Label Noise—0
Shifted Chunk Transformer for Spatio-Temporal Representational Learning—0
Consistent Relative Confidence and Label-Free Model Selection for Convolutional Neural Networks—0
Auxiliary Task Update Decomposition: The Good, The Bad and The NeutralCode0
NGC: A Unified Framework for Learning with Open-World Noisy Data—0
Understanding the Generalization of Adam in Learning Neural Networks with Proper Regularization—0
MCUa: Multi-level Context and Uncertainty aware Dynamic Deep Ensemble for Breast Cancer Histology Image ClassificationCode0
Improving Generalization of Batch Whitening by Convolutional Unit OptimizationCode0
ProtoMIL: Multiple Instance Learning with Prototypical Parts for Whole-Slide Image ClassificationCode0
CE-Dedup: Cost-Effective Convolutional Neural Nets Training based on Image Deduplication—0
How Transferable Are Self-supervised Features in Medical Image Classification Tasks?—0
Fusion of evidential CNN classifiers for image classification—0
Training and Profiling a Pediatric Emotion Recognition Classifier on Mobile Devices—0
Spatial Transformer Networks for Curriculum Learning—0
Ensemble of CNN classifiers using Sugeno Fuzzy Integral Technique for Cervical Cytology Image Classification—0
A Novel Solution of an Elastic Net Regularization for Dementia Knowledge Discovery using Deep Learning—0
SERF: Towards better training of deep neural networks using log-Softplus ERror activation Function—0
Early-exit deep neural networks for distorted images: providing an efficient edge offloadingCode0
Semi-supervised learning for medical image classification using imbalanced training data—0
Comparing concepts of quantum and classical neural network models for image classification task—0
Classification and reconstruction of spatially overlapping phase images using diffractive optical networks—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