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 8301–8325 of 10420 papers

TitleStatusHype
Debiasing Classifiers by Amplifying Bias with Latent Diffusion and Large Language Models—0
DebugAgent: Efficient and Interpretable Error Slice Discovery for Comprehensive Model Debugging—0
Deceiving Google's Cloud Video Intelligence API Built for Summarizing Videos—0
Deceiving Image-to-Image Translation Networks for Autonomous Driving with Adversarial Perturbations—0
Decentralized Federated Learning Over Imperfect Communication Channels—0
Decentralized Federated Learning with Gradient Tracking over Time-Varying Directed Networks—0
Decentralized SGD with Over-the-Air Computation—0
Decision boundaries and convex hulls in the feature space that deep learning functions learn from images—0
Decision Propagation Networks for Image Classification—0
Decision Tree Learning with Spatial Modal Logics—0
Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features—0
Decomposing Convolutional Neural Networks into Reusable and Replaceable Modules—0
Decomposition-Based Transfer Distance Metric Learning for Image Classification—0
Decoupled Greedy Learning of CNNs for Synchronous and Asynchronous Distributed Learning—0
Decoupling Feature Extraction and Classification Layers for Calibrated Neural Networks—0
Deep Active Ensemble Sampling For Image Classification—0
Does Deep Active Learning Work in the Wild?—0
Deep Active Learning in the Open World—0
Deep Active Learning in the Presence of Label Noise: A Survey—0
Deep Adaptive Semantic Logic (DASL): Compiling Declarative Knowledge into Deep Neural Networks—0
DeepAGREL: Biologically plausible deep learning via direct reinforcement—0
Deep Algorithmic Question Answering: Towards a Compositionally Hybrid AI for Algorithmic Reasoning—0
Deep Attributes from Context-Aware Regional Neural Codes—0
Deep AUC Maximization for Medical Image Classification: Challenges and Opportunities—0
Deep Autoencoder Model Construction Based on Pytorch—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