SOTAVerified

General Classification

Algorithms trying to solve the general task of classification.

Papers

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Showing 4376–4400 of 14581 papers

TitleStatusHype
Rethinking Skip-thought: A Neighborhood based Approach—0
Rethinking the Faster R-CNN Architecture for Temporal Action Localization—0
Retinal Fluid Segmentation and Detection in Optical Coherence Tomography Images using Fully Convolutional Neural Network—0
Returning the N to NLP: Towards Contextually Personalized Classification Models—0
Reusing Neural Speech Representations for Auditory Emotion Recognition—0
Revealing Fundamental Physics from the Daya Bay Neutrino Experiment using Deep Neural Networks—0
Reverse Classification Accuracy: Predicting Segmentation Performance in the Absence of Ground Truth—0
Reversed Active Learning based Atrous DenseNet for Pathological Image Classification—0
Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics—0
Reverse Multi-Label Learning—0
Unauthorized AI cannot Recognize Me: Reversible Adversarial Example—0
Review-Level Sentiment Classification with Sentence-Level Polarity Correction—0
Supervised Momentum Contrastive Learning for Few-Shot Classification—0
Revisiting convolutional neural network on graphs with polynomial approximations of Laplace-Beltrami spectral filtering—0
Revisiting Dilated Convolution: A Simple Approach for Weakly- and Semi-Supervised Semantic Segmentation—0
Revisiting ( , , )-similarity learning for domain adaptation—0
Revisiting Few-shot Relation Classification: Evaluation Data and Classification Schemes—0
Revisiting Graph Convolutional Network on Semi-Supervised Node Classification from an Optimization Perspective—0
Revisiting Human Action Recognition: Personalization vs. Generalization—0
Revisiting IM2GPS in the Deep Learning Era—0
Revisiting Metric Learning for Few-Shot Image Classification—0
Revisiting MLLMs: An In-Depth Analysis of Image Classification Abilities—0
A Simple Non-i.i.d. Sampling Approach for Efficient Training and Better Generalization—0
Revisiting the Effectiveness of Off-the-shelf Temporal Modeling Approaches for Large-scale Video Classification—0
Revisiting the Importance of Individual Units in CNNs via Ablation—0
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All datasetsXORirisActivityFashion-MNISTISOLETMice ProteinMNISTWine

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1KNNAccuracy93.1—Unverified
2RFAccuracy92.96—Unverified
3CARTAccuracy92.82—Unverified
4LDAAccuracy77.22—Unverified
#ModelMetricClaimedVerifiedStatus
1MONT3Accuracy100—Unverified
2XBNETAccuracy100—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy42—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy67.7—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy68.5—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy13.4—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy90.6—Unverified
#ModelMetricClaimedVerifiedStatus
1MONT3Accuracy100—Unverified