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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 151–200 of 12815 papers

Title	Date	Tasks	Status	Hype	Score
A graph-transformer for whole slide image classification	May 19, 2022	ClassificationContrastive Learning	CodeCode Available	1	5
Beyond single receptive field: A receptive field fusion-and-stratification network for airborne laser scanning point cloud classification	Jul 21, 2022	ClassificationPoint Cloud Classification	CodeCode Available	1	5
Billion-scale semi-supervised learning for image classification	May 2, 2019	ClassificationGeneral Classification	CodeCode Available	1	5
EEG-based Emotional Video Classification via Learning Connectivity Structure	May 28, 2019	ClassificationEEG	CodeCode Available	1	5
Can multi-label classification networks know what they don't know?	Sep 29, 2021	ClassificationMulti-class Classification	CodeCode Available	1	5
Classification of Edge-dependent Labels of Nodes in Hypergraphs	Jun 5, 2023	ClassificationNode Clustering	CodeCode Available	1	5
Benchmarking and Analyzing Point Cloud Classification under Corruptions	Feb 7, 2022	BenchmarkingClassification	CodeCode Available	1	5
Benchmarking Adversarial Robustness on Image Classification	Jun 1, 2020	Adversarial AttackAdversarial Robustness	CodeCode Available	1	5
Benchmarking Self-Supervised Learning on Diverse Pathology Datasets	Dec 9, 2022	BenchmarkingClassification	CodeCode Available	1	5
Bearing Fault Diagnosis Base on Multi-scale CNN and LSTM Model	Jun 5, 2020	ClassificationDiagnostic	CodeCode Available	1	5
Adversarial examples for generative models	Feb 22, 2017	ClassificationGeneral Classification	CodeCode Available	1	5
Bamboo: Building Mega-Scale Vision Dataset Continually with Human-Machine Synergy	Mar 15, 2022	Active LearningClassification	CodeCode Available	1	5
Be More with Less: Hypergraph Attention Networks for Inductive Text Classification	Nov 1, 2020	ClassificationGeneral Classification	CodeCode Available	1	5
Are We Really Making Much Progress in Text Classification? A Comparative Review	Apr 8, 2022	ClassificationDecoder	CodeCode Available	1	5
Adversarial Deep Network Embedding for Cross-network Node Classification	Feb 18, 2020	ClassificationDomain Adaptation	CodeCode Available	1	5
Balanced Energy Regularization Loss for Out-of-distribution Detection	Jun 18, 2023	Classificationimage-classification	CodeCode Available	1	5
BAdaCost: Multi-class Boosting with Costs	Feb 6, 2024	ClassificationMulti-class Classification	CodeCode Available	1	5
Adversarial Attacks on Graph Classifiers via Bayesian Optimisation	Dec 1, 2021	Adversarial RobustnessBayesian Optimisation	CodeCode Available	1	5
Bacteriophage classification for assembled contigs using Graph Convolutional Network	Feb 7, 2021	ClassificationDiversity	CodeCode Available	1	5
Balanced-MixUp for Highly Imbalanced Medical Image Classification	Sep 20, 2021	Classificationimage-classification	CodeCode Available	1	5
BertGCN: Transductive Text Classification by Combining GCN and BERT	May 12, 2021	Classificationtext-classification	CodeCode Available	1	5
Automatic Severity Classification of Dysarthric speech by using Self-supervised Model with Multi-task Learning	Oct 27, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	CodeCode Available	1	5
Automatic Recognition of Abdominal Organs in Ultrasound Images based on Deep Neural Networks and K-Nearest-Neighbor Classification	Oct 9, 2021	ClassificationDimensionality Reduction	CodeCode Available	1	5
AutoMix: Unveiling the Power of Mixup for Stronger Classifiers	Mar 24, 2021	ClassificationData Augmentation	CodeCode Available	1	5
Self-Supervised Graph Neural Networks for Improved Electroencephalographic Seizure Analysis	Apr 16, 2021	ClassificationEEG	CodeCode Available	1	5
Background Data Resampling for Outlier-Aware Classification	Jun 1, 2020	ClassificationGeneral Classification	CodeCode Available	1	5
3DCTN: 3D Convolution-Transformer Network for Point Cloud Classification	Mar 2, 2022	ClassificationPoint Cloud Classification	CodeCode Available	1	5
Adversarial Attacks on Graph Classification via Bayesian Optimisation	Nov 4, 2021	Adversarial RobustnessBayesian Optimisation	CodeCode Available	1	5
3D Deformable Convolutions for MRI classification	Nov 5, 2019	ClassificationGeneral Classification	CodeCode Available	1	5
Adversarial Attacks on Time Series	Feb 27, 2019	ClassificationDynamic Time Warping	CodeCode Available	1	5
Adversarial AutoMixup	Dec 19, 2023	Classificationimage-classification	CodeCode Available	1	5
Bag of Tricks for Node Classification with Graph Neural Networks	Mar 24, 2021	ClassificationGeneral Classification	CodeCode Available	1	5
Automatically designing CNN architectures using genetic algorithm for image classification	Aug 11, 2018	ClassificationGeneral Classification	CodeCode Available	1	5
Adversarial Feature Augmentation and Normalization for Visual Recognition	Mar 22, 2021	ClassificationData Augmentation	CodeCode Available	1	5
Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma Augmented Gaussian Processes	Jul 20, 2020	ClassificationGaussian Processes	CodeCode Available	1	5
BCN: Batch Channel Normalization for Image Classification	Dec 1, 2023	Classificationimage-classification	CodeCode Available	1	5
Adversarial Feature Augmentation for Cross-domain Few-shot Classification	Aug 23, 2022	ClassificationCross-Domain Few-Shot	CodeCode Available	1	5
Adversarial Policy Gradient for Deep Learning Image Augmentation	Sep 9, 2019	ClassificationDeep Learning	CodeCode Available	1	5
AutoML4ETC: Automated Neural Architecture Search for Real-World Encrypted Traffic Classification	Aug 4, 2023	ClassificationEarly Classification	CodeCode Available	1	5
Adversarially-Trained Deep Nets Transfer Better: Illustration on Image Classification	Jul 11, 2020	ClassificationGeneral Classification	CodeCode Available	1	5
AEDA: An Easier Data Augmentation Technique for Text Classification	Aug 30, 2021	ClassificationData Augmentation	CodeCode Available	1	5
A Dynamic Weighted Federated Learning for Android Malware Classification	Nov 23, 2022	ClassificationFederated Learning	CodeCode Available	1	5
A Fast 3D CNN for Hyperspectral Image Classification	Apr 29, 2020	ClassificationGeneral Classification	CodeCode Available	1	5
A Diagnostic Study of Explainability Techniques for Text Classification	Sep 25, 2020	ClassificationDiagnostic	CodeCode Available	1	5
A Fully Hyperbolic Neural Model for Hierarchical Multi-Class Classification	Oct 5, 2020	ClassificationEntity Typing	CodeCode Available	1	5
Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting	Jan 27, 2019	ClassificationGeneral Classification	CodeCode Available	1	5
The MAMe Dataset: On the relevance of High Resolution and Variable Shape image properties	Jul 27, 2020	ClassificationGeneral Classification	CodeCode Available	1	5
African or European Swallow? Benchmarking Large Vision-Language Models for Fine-Grained Object Classification	Jun 20, 2024	BenchmarkingClassification	CodeCode Available	1	5
Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization	May 24, 2024	ClassificationFederated Learning	CodeCode Available	1	5
BootAug: Boosting Text Augmentation via Hybrid Instance Filtering Framework	Oct 6, 2022	ClassificationData Augmentation	CodeCode Available	1	5

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All datasets InDL MHIST N-ImageNet SPOT-10 Full-body Parkinson’s disease dataset Autoimmune Dataset N-CARS N-ImageNet (mini)ImageNet C-OOD (class-out-of-distribution)CWRU Bearing Dataset Burr classification images ForgeryNet

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	ConvNext	Average Recall	93.47	—	Unverified
2	VGG16	Average Recall	92.86	—	Unverified
3	DenseNet201	Average Recall	90.99	—	Unverified
4	Inception ResNet V2	Average Recall	90.27	—	Unverified
5	Xception	Average Recall	89.81	—	Unverified
6	NASNetLarge	Average Recall	89.52	—	Unverified
7	Darknet53	Average Recall	88.53	—	Unverified
8	ResNetV2_50	Average Recall	88.08	—	Unverified
9	MobileNetV3	Average Recall	84.28	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MoCo-v2 (ResNet-50)	Accuracy	88.03	—	Unverified
2	MoCo-v2 (ResNet-50)	Accuracy	85.88	—	Unverified
3	Barlow Twins (ResNet-50)	Accuracy	84.03	—	Unverified
4	SwAV (ResNet-50)	Accuracy	83.21	—	Unverified
5	Supervised (ViT-S/16)	Accuracy	81.68	—	Unverified
6	Barlow Rwins (ResNet-50)	Accuracy	81.27	—	Unverified
7	DINO (ViT-S/16)	Accuracy	79.43	—	Unverified
8	Supervised (ResNet-50)	Accuracy	78.92	—	Unverified
9	SwAV (ResNet-50)	Accuracy	77.99	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Event Spike Tensor	Accuracy (%)	48.93	—	Unverified
2	DiST	Accuracy (%)	48.43	—	Unverified
3	Sorted Time Surface	Accuracy (%)	47.9	—	Unverified
4	Event Histogram	Accuracy (%)	47.73	—	Unverified
5	HATS	Accuracy (%)	47.14	—	Unverified
6	Binary Event Image	Accuracy (%)	46.36	—	Unverified
7	Timestamp Image	Accuracy (%)	45.86	—	Unverified
8	Event Image	Accuracy (%)	45.77	—	Unverified
9	Time Surface	Accuracy (%)	44.32	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DenseNet121 Distiller	Accuracy	81.84	—	Unverified
2	ResNet101V2 Distiller	Accuracy	80.29	—	Unverified
3	ResNet50V2 Distiller	Accuracy	79.03	—	Unverified
4	MobileNet Distiller	Accuracy	78.26	—	Unverified
5	MobileNetV3Small Distiller	Accuracy	78.04	—	Unverified
6	MobileNetV3Large Distiller	Accuracy	77.88	—	Unverified
7	NASNetMobile Distiller	Accuracy	77.75	—	Unverified
8	MobileNetV2 Distiller	Accuracy	77.53	—	Unverified
9	ResNet50 Distiller	Accuracy	77.45	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PoseFormerV2	F1-score (weighted)	0.59	—	Unverified
2	PD STGCN	F1-score (weighted)	0.48	—	Unverified
3	MotionBERT	F1-score (weighted)	0.47	—	Unverified
4	Pose Transformers (POTR)	F1-score (weighted)	0.46	—	Unverified
5	MotionBERT-LITE	F1-score (weighted)	0.43	—	Unverified
6	MotionAGFormer	F1-score (weighted)	0.42	—	Unverified
7	Mixste	F1-score (weighted)	0.41	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Swin Transformer Base (Patch 4 Window 12)	F1 score	0.89	—	Unverified
2	CASS	F1 score	0.89	—	Unverified
3	CASS	F1 score	0.87	—	Unverified
4	DINO	F1 score	0.86	—	Unverified
5	DINO	F1 score	0.84	—	Unverified
6	VANBUREN et all	F1 score	0.63	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MEM	Accuracy (%)	98.55	—	Unverified
2	GET	Accuracy (%)	96.7	—	Unverified
3	ResNet34 + EST	Accuracy (%)	92.5	—	Unverified
4	Spiking VGG-11	Accuracy (%)	92.4	—	Unverified
5	Spiking MobileNet-64	Accuracy (%)	91.7	—	Unverified
6	Spiking DenseNet121-24	Accuracy (%)	90.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Event Imge	Accuracy (%)	61.42	—	Unverified
2	Event Histogram	Accuracy (%)	61.02	—	Unverified
3	Timestamp Image	Accuracy (%)	60.46	—	Unverified
4	DiST	Accuracy (%)	59.74	—	Unverified
5	Sorted Time Surface	Accuracy (%)	58.38	—	Unverified
6	Binary Event Image	Accuracy (%)	53.52	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ViT-L/32-384 with Max-logit	Detection AUROC (severity 0)	1	—	Unverified
2	ViT-L/32-384 with ODIN	Detection AUROC (severity 0)	1	—	Unverified
3	ViT-L/32-384 with Entropy	Detection AUROC (severity 0)	0.99	—	Unverified
4	ViT-L/32-384 with MC Dropout	Detection AUROC (severity 0)	0.99	—	Unverified
5	ViT-L/32-384 with Softmax	Detection AUROC (severity 0)	0.99	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MixMamba-Fewshot	10 fold Cross validation	99.93	—	Unverified
2	Few-shot Transformer Covariance	10 fold Cross validation	99.86	—	Unverified
3	MCNN-LSTM	10 fold Cross validation	98.46	—	Unverified
4	CNN	10 fold Cross validation	7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	70_divisions	precision	93.2	—	Unverified
2	60_divisions	precision	93.2	—	Unverified
3	80_divisions	precision	93.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MINTIME-XC	AUC	94.25	—	Unverified
2	SlowFast R-50	AUC	90.86	—	Unverified
3	MINTIME-EF	AUC	90.45	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DenseNet121	Robustness Score	0.91	—	Unverified
2	ResNet 50	Robustness Score	0.9	—	Unverified
3	VGG-16	Robustness Score	0.88	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BIOSCAN_1M_order_classifier	Macro F1	92.65	—	Unverified
2	BIOSCAN_1M_family_classifier	Macro F1	91.45	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	OPT-1.3B	Test Accuracy	62.5	—	Unverified
2	OPT-125M	Test Accuracy	61.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	OPT-1.3B	Test Accuracy	75.71	—	Unverified
2	OPT-125M	Test Accuracy	75	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GPT-4	1 shot Micro-F1	96.86	—	Unverified
2	BiLSTM-CRF	1 shot Micro-F1	82.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SVM	F1-score (Weighted)	86.19	—	Unverified
2	RoBERTa	F1-score (Weighted)	78.13	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	GLNet	1:1 Accuracy	95.07	—	Unverified
2	CPM	1:1 Accuracy	50	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	OPT-1.3B	Test Accuracy	60.89	—	Unverified
2	OPT-125M	Test Accuracy	57.05	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ELM Neuron	Accuracy (%)	82	—	Unverified
2	LSTM	Accuracy (%)	10	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	OPT-1.3B	Test Accuracy	90.78	—	Unverified
2	OPT-125M	Test Accuracy	85.08	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	OPT-1.3B	Test Accuracy	56.14	—	Unverified
2	OPT-125M	Test Accuracy	53.38	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	OPT-1.3B	Test Accuracy	64.16	—	Unverified
2	OPT-125M	Test Accuracy	59.59	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MambaNet	AUROC	0.91	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RandomForestClassifier	Accuracy	82	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CNN + Attention + LSTM + CNN	Accuracy (%)	86.91	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	WeaSEL	1:1 Accuracy	86	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DINO	F1 score	0.99	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	AAPSO-Deep Feature Selection	Accuracy	98.41	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CNN	Validation Accuracy	93.55	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ResNet8×4	Accuracy	77.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ViT-L/16 (Background)	Accuracy on Brightness Corrupted Images	99.03	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Random Forest	AUC	0.97	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	lstm	Accuracy	0.72	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MSTP	Accuracy	95.11	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RECALL	Overall accuracy after last sequence	57.83	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RECALL	Overall accuracy after last sequence	4,065	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RRWNet	Accuracy	0.98	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TD-CNN- Attention	F1 score	99.71	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CLIP-RN50x64	1-of-100 Accuracy	61	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SVM	F1 (%)	97.72	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RRWNet	Accuracy	0.95	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	HSQformer	AUC	83.83	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	WaferSegClassNet	Accuracy	0.98	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	C-Tran, preprocessing, augmentation	ML F1	0.57	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	μ RadNet	1:1 Accuracy	99.22	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Resnet 50	Accuracy (% )	92.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RRWNet	Accuracy	0.97	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	pFedBreD_ns_mg	Accuracy	73.81	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SGD_ss	F1 (Seqeval)	2,020	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LangGas	Frame Level Accuracy	0.89	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	1DCNN-ResNet	macro f1 score (A(100), B(100), C(100) Avg.)	0.99	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BRIDGE	Accuracy	25.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MSI-H Transformer	AUPRC	0.58	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BRIDGE	Accuracy	42.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BRIDGE	Accuracy	36.2	—	Unverified