SOTAVerified

General Classification

Algorithms trying to solve the general task of classification.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 8901–8925 of 14581 papers

TitleStatusHype
Adaptive Diffusions for Scalable Learning over Graphs—0
Identifying Cross-Depicted Historical Motifs—0
An integration of fast alignment and maximum-likelihood methods for electron subtomogram averaging and classification—0
Improving Classification Rate of Schizophrenia Using a Multimodal Multi-Layer Perceptron Model with Structural and Functional MR—0
Online Multi-Label Classification: A Label Compression Method—0
StainGAN: Stain Style Transfer for Digital Histological ImagesCode0
Weakly Supervised Instance Segmentation using Class Peak ResponseCode0
Unsupervised Semantic-based Aggregation of Deep Convolutional FeaturesCode1
Multi-Scale Spatially-Asymmetric Recalibration for Image Classification—0
EmoRL: Continuous Acoustic Emotion Classification using Deep Reinforcement Learning—0
Incorporating Word Embeddings into Open Directory Project based Large-scale Classification—0
Analysis on the Nonlinear Dynamics of Deep Neural Networks: Topological Entropy and Chaos—0
Hospital Readmission Prediction - Applying Hierarchical Sparsity Norms for Interpretable Models—0
AttnConvnet at SemEval-2018 Task 1: Attention-based Convolutional Neural Networks for Multi-label Emotion Classification—0
Deep Spatiotemporal Models for Robust Proprioceptive Terrain Classification—0
Confidence from Invariance to Image TransformationsCode0
Speaker-Invariant Training via Adversarial Learning—0
Multi-scale Location-aware Kernel Representation for Object DetectionCode0
Learning Latent Opinions for Aspect-Level Sentiment ClassificationCode0
SampleAhead: Online Classifier-Sampler Communication for Learning from Synthesized Data—0
Attentional Multilabel Learning over Graphs: A Message Passing Approach—0
Webly Supervised Learning for Skin Lesion Classification—0
In-depth Question classification using Convolutional Neural Networks—0
Automatically augmenting an emotion dataset improves classification using audio—0
Engineering a Simplified 0-Bit Consistent Weighted Sampling—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
1XBNETAccuracy100—Unverified
2MONT3Accuracy100—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy42—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy67.7—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy68.5—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy13.4—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy90.6—Unverified
#ModelMetricClaimedVerifiedStatus
1MONT3Accuracy100—Unverified