SOTAVerified

Classification

Classification is the task of categorizing a set of data into predefined classes or groups. The aim of classification is to train a model to correctly predict the class or group of new, unseen data. The model is trained on a labeled dataset where each instance is assigned a class label. The learning algorithm then builds a mapping between the features of the data and the class labels. This mapping is then used to predict the class label of new, unseen data points. The quality of the prediction is usually evaluated using metrics such as accuracy, precision, and recall.

Papers

Showing 45514600 of 12815 papers

TitleStatusHype
Learning Multi-level Deep Representations for Image Emotion Classification0
Learning Multi-Scale Representations for Material Classification0
Learning Muti-expert Distribution Calibration for Long-tailed Video Classification0
Learning Nigerian accent embeddings from speech: preliminary results based on SautiDB-Naija corpus0
Learning Non-Linear Functions for Text Classification0
Learning Non-Linear Reconstruction Models for Image Set Classification0
Learning on Random Balls is Sufficient for Estimating (Some) Graph Parameters0
Learning Optimal Classification Trees Robust to Distribution Shifts0
Learning Optimal Classification Trees: Strong Max-Flow Formulations0
Learning Optimal Fair Scoring Systems for Multi-Class Classification0
Learning Optimal Signal Temporal Logic Decision Trees for Classification: A Max-Flow MILP Formulation0
Learning rates for classification with Gaussian kernels0
Learning Receptive Fields for Pooling from Tensors of Feature Response0
Reliable Representations Learning for Incomplete Multi-View Partial Multi-Label Classification0
Learning representations for sentiment classification using Multi-task framework0
Learning Representations of Missing Data for Predicting Patient Outcomes0
Learning rich optical embeddings for privacy-preserving lensless image classification0
Learning Robust, Transferable Sentence Representations for Text Classification0
Learning Sampling Policies for Domain Adaptation0
Learning Schizophrenia Imaging Genetics Data Via Multiple Kernel Canonical Correlation Analysis0
Learning Section Weights for Multi-Label Document Classification0
Learning Sentence Representations over Tree Structures for Target-Dependent Classification0
Learning Social Image Embedding with Deep Multimodal Attention Networks0
Learning Sparse Adversarial Dictionaries For Multi-Class Audio Classification0
Learning spatio-temporal representations with temporal squeeze pooling0
Learning Strategies for Radar Clutter Classification0
Learning Structured Low-Rank Representations for Image Classification0
Learning Structures for Deep Neural Networks0
Learning Subclass Representations for Visually-varied Image Classification0
Learning Subject-Invariant Representations from Speech-Evoked EEG Using Variational Autoencoders0
Learning Supervised Topic Models for Classification and Regression from Crowds0
Learning the Kernel for Classification and Regression0
Learning Through Guidance: Knowledge Distillation for Endoscopic Image Classification0
Learning to Adapt Domain Shifts of Moral Values via Instance Weighting0
Learning to Combat Noisy Labels via Classification Margins0
Learning to Compose Diversified Prompts for Image Emotion Classification0
Learning to Control the Smoothness of Graph Convolutional Network Features0
Learning to Detect Adversarial Examples Based on Class Scores0
Learning to Explicitate Connectives with Seq2Seq Network for Implicit Discourse Relation Classification0
Learning to Find Correlated Features by Maximizing Information Flow in Convolutional Neural Networks0
Learning to Generalize to Unseen Tasks with Bilevel Optimization0
CinPatent: Datasets for Patent Classification0
Learning to Learn and Predict: A Meta-Learning Approach for Multi-Label Classification0
Learning to Learn Image Classifiers with Visual Analogy0
Learning to Learn Semantic Factors in Heterogeneous Image Classification0
Learning to rumble: Automated elephant call classification, detection and endpointing using deep architectures0
Learning to segment images with classification labels0
Learning to Select Base Classes for Few-shot Classification0
Land-Cover Classification with High-Resolution Remote Sensing Images Using Transferable Deep Models0
Learning Transformations for Classification Forests0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ConvNextAverage Recall93.47Unverified
2VGG16Average Recall92.86Unverified
3DenseNet201Average Recall90.99Unverified
4Inception ResNet V2Average Recall90.27Unverified
5XceptionAverage Recall89.81Unverified
6NASNetLargeAverage Recall89.52Unverified
7Darknet53Average Recall88.53Unverified
8ResNetV2_50Average Recall88.08Unverified
9MobileNetV3Average Recall84.28Unverified
#ModelMetricClaimedVerifiedStatus
1MoCo-v2 (ResNet-50)Accuracy88.03Unverified
2MoCo-v2 (ResNet-50)Accuracy85.88Unverified
3Barlow Twins (ResNet-50)Accuracy84.03Unverified
4SwAV (ResNet-50)Accuracy83.21Unverified
5Supervised (ViT-S/16)Accuracy81.68Unverified
6Barlow Rwins (ResNet-50)Accuracy81.27Unverified
7DINO (ViT-S/16)Accuracy79.43Unverified
8Supervised (ResNet-50)Accuracy78.92Unverified
9SwAV (ResNet-50)Accuracy77.99Unverified
#ModelMetricClaimedVerifiedStatus
1Event Spike TensorAccuracy (%)48.93Unverified
2DiSTAccuracy (%)48.43Unverified
3Sorted Time SurfaceAccuracy (%)47.9Unverified
4Event HistogramAccuracy (%)47.73Unverified
5HATSAccuracy (%)47.14Unverified
6Binary Event ImageAccuracy (%)46.36Unverified
7Timestamp ImageAccuracy (%)45.86Unverified
8Event ImageAccuracy (%)45.77Unverified
9Time SurfaceAccuracy (%)44.32Unverified
#ModelMetricClaimedVerifiedStatus
1DenseNet121 DistillerAccuracy81.84Unverified
2ResNet101V2 DistillerAccuracy80.29Unverified
3ResNet50V2 DistillerAccuracy79.03Unverified
4MobileNet DistillerAccuracy78.26Unverified
5MobileNetV3Small DistillerAccuracy78.04Unverified
6MobileNetV3Large DistillerAccuracy77.88Unverified
7NASNetMobile DistillerAccuracy77.75Unverified
8MobileNetV2 DistillerAccuracy77.53Unverified
9ResNet50 DistillerAccuracy77.45Unverified
#ModelMetricClaimedVerifiedStatus
1PoseFormerV2F1-score (weighted)0.59Unverified
2PD STGCNF1-score (weighted)0.48Unverified
3MotionBERTF1-score (weighted)0.47Unverified
4Pose Transformers (POTR)F1-score (weighted)0.46Unverified
5MotionBERT-LITEF1-score (weighted)0.43Unverified
6MotionAGFormerF1-score (weighted)0.42Unverified
7MixsteF1-score (weighted)0.41Unverified
#ModelMetricClaimedVerifiedStatus
1Swin Transformer Base (Patch 4 Window 12)F1 score0.89Unverified
2CASSF1 score0.89Unverified
3CASSF1 score0.87Unverified
4DINOF1 score0.86Unverified
5DINOF1 score0.84Unverified
6VANBUREN et allF1 score0.63Unverified
#ModelMetricClaimedVerifiedStatus
1MEMAccuracy (%)98.55Unverified
2GETAccuracy (%)96.7Unverified
3ResNet34 + ESTAccuracy (%)92.5Unverified
4Spiking VGG-11Accuracy (%)92.4Unverified
5Spiking MobileNet-64Accuracy (%)91.7Unverified
6Spiking DenseNet121-24Accuracy (%)90.4Unverified
#ModelMetricClaimedVerifiedStatus
1Event ImgeAccuracy (%)61.42Unverified
2Event HistogramAccuracy (%)61.02Unverified
3Timestamp ImageAccuracy (%)60.46Unverified
4DiSTAccuracy (%)59.74Unverified
5Sorted Time SurfaceAccuracy (%)58.38Unverified
6Binary Event ImageAccuracy (%)53.52Unverified
#ModelMetricClaimedVerifiedStatus
1ViT-L/32-384 with Max-logitDetection AUROC (severity 0)1Unverified
2ViT-L/32-384 with ODINDetection AUROC (severity 0)1Unverified
3ViT-L/32-384 with EntropyDetection AUROC (severity 0)0.99Unverified
4ViT-L/32-384 with MC DropoutDetection AUROC (severity 0)0.99Unverified
5ViT-L/32-384 with SoftmaxDetection AUROC (severity 0)0.99Unverified
#ModelMetricClaimedVerifiedStatus
1MixMamba-Fewshot10 fold Cross validation99.93Unverified
2Few-shot Transformer Covariance10 fold Cross validation99.86Unverified
3MCNN-LSTM10 fold Cross validation98.46Unverified
4CNN10 fold Cross validation7Unverified
#ModelMetricClaimedVerifiedStatus
170_divisionsprecision93.2Unverified
260_divisionsprecision93.2Unverified
380_divisionsprecision93.2Unverified
#ModelMetricClaimedVerifiedStatus
1MINTIME-XCAUC94.25Unverified
2SlowFast R-50AUC90.86Unverified
3MINTIME-EFAUC90.45Unverified
#ModelMetricClaimedVerifiedStatus
1DenseNet121Robustness Score0.91Unverified
2ResNet 50Robustness Score0.9Unverified
3VGG-16Robustness Score0.88Unverified
#ModelMetricClaimedVerifiedStatus
1BIOSCAN_1M_order_classifierMacro F192.65Unverified
2BIOSCAN_1M_family_classifierMacro F191.45Unverified
#ModelMetricClaimedVerifiedStatus
1OPT-1.3BTest Accuracy62.5Unverified
2OPT-125MTest Accuracy61.6Unverified
#ModelMetricClaimedVerifiedStatus
1OPT-1.3BTest Accuracy75.71Unverified
2OPT-125MTest Accuracy75Unverified
#ModelMetricClaimedVerifiedStatus
1GPT-41 shot Micro-F196.86Unverified
2BiLSTM-CRF1 shot Micro-F182.2Unverified
#ModelMetricClaimedVerifiedStatus
1SVMF1-score (Weighted)86.19Unverified
2RoBERTaF1-score (Weighted)78.13Unverified
#ModelMetricClaimedVerifiedStatus
1GLNet1:1 Accuracy95.07Unverified
2CPM1:1 Accuracy50Unverified
#ModelMetricClaimedVerifiedStatus
1OPT-1.3BTest Accuracy60.89Unverified
2OPT-125MTest Accuracy57.05Unverified
#ModelMetricClaimedVerifiedStatus
1ELM NeuronAccuracy (%)82Unverified
2LSTMAccuracy (%)10Unverified
#ModelMetricClaimedVerifiedStatus
1OPT-1.3BTest Accuracy90.78Unverified
2OPT-125MTest Accuracy85.08Unverified
#ModelMetricClaimedVerifiedStatus
1OPT-1.3BTest Accuracy56.14Unverified
2OPT-125MTest Accuracy53.38Unverified
#ModelMetricClaimedVerifiedStatus
1OPT-1.3BTest Accuracy64.16Unverified
2OPT-125MTest Accuracy59.59Unverified
#ModelMetricClaimedVerifiedStatus
1MambaNetAUROC0.91Unverified
#ModelMetricClaimedVerifiedStatus
1RandomForestClassifierAccuracy82Unverified
#ModelMetricClaimedVerifiedStatus
1CNN + Attention + LSTM + CNNAccuracy (%)86.91Unverified
#ModelMetricClaimedVerifiedStatus
1WeaSEL1:1 Accuracy86Unverified
#ModelMetricClaimedVerifiedStatus
1DINOF1 score0.99Unverified
#ModelMetricClaimedVerifiedStatus
1AAPSO-Deep Feature SelectionAccuracy98.41Unverified
#ModelMetricClaimedVerifiedStatus
1CNNValidation Accuracy93.55Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet8×4Accuracy77.5Unverified
#ModelMetricClaimedVerifiedStatus
1ViT-L/16 (Background)Accuracy on Brightness Corrupted Images99.03Unverified
#ModelMetricClaimedVerifiedStatus
1Random ForestAUC0.97Unverified
#ModelMetricClaimedVerifiedStatus
1lstmAccuracy0.72Unverified
#ModelMetricClaimedVerifiedStatus
1MSTPAccuracy95.11Unverified
#ModelMetricClaimedVerifiedStatus
1RECALLOverall accuracy after last sequence57.83Unverified
#ModelMetricClaimedVerifiedStatus
1RECALLOverall accuracy after last sequence4,065Unverified
#ModelMetricClaimedVerifiedStatus
1RRWNetAccuracy0.98Unverified
#ModelMetricClaimedVerifiedStatus
1TD-CNN- AttentionF1 score99.71Unverified
#ModelMetricClaimedVerifiedStatus
1CLIP-RN50x641-of-100 Accuracy61Unverified
#ModelMetricClaimedVerifiedStatus
1SVMF1 (%)97.72Unverified
#ModelMetricClaimedVerifiedStatus
1RRWNetAccuracy0.95Unverified
#ModelMetricClaimedVerifiedStatus
1HSQformerAUC83.83Unverified
#ModelMetricClaimedVerifiedStatus
1WaferSegClassNetAccuracy0.98Unverified
#ModelMetricClaimedVerifiedStatus
1C-Tran, preprocessing, augmentationML F10.57Unverified
#ModelMetricClaimedVerifiedStatus
1μ RadNet1:1 Accuracy99.22Unverified
#ModelMetricClaimedVerifiedStatus
1Resnet 50Accuracy (% )92.5Unverified
#ModelMetricClaimedVerifiedStatus
1RRWNetAccuracy0.97Unverified
#ModelMetricClaimedVerifiedStatus
1pFedBreD_ns_mgAccuracy73.81Unverified
#ModelMetricClaimedVerifiedStatus
1SGD_ssF1 (Seqeval)2,020Unverified
#ModelMetricClaimedVerifiedStatus
1LangGasFrame Level Accuracy0.89Unverified
#ModelMetricClaimedVerifiedStatus
11DCNN-ResNetmacro f1 score (A(100), B(100), C(100) Avg.)0.99Unverified
#ModelMetricClaimedVerifiedStatus
1BRIDGEAccuracy25.6Unverified
#ModelMetricClaimedVerifiedStatus
1MSI-H TransformerAUPRC0.58Unverified
#ModelMetricClaimedVerifiedStatus
1BRIDGEAccuracy42.2Unverified
#ModelMetricClaimedVerifiedStatus
1BRIDGEAccuracy36.2Unverified