2025
scMODAL: a general deep learning framework for comprehensive single-cell multi-omics data alignment with feature links
Wang G, Zhao J, Lin Y, Liu T, Zhao Y, Zhao H. scMODAL: a general deep learning framework for comprehensive single-cell multi-omics data alignment with feature links. Nature Communications 2025, 16: 4994. PMID: 40442129, PMCID: PMC12122792, DOI: 10.1038/s41467-025-60333-z.Peer-Reviewed Original ResearchConceptsDeep learning frameworkSingle-cell multi-omics researchSingle-cell multi-omics dataLearning frameworkMulti-omics dataGenerative adversarial networkSingle-cell technologiesData alignmentSingle-cell resolutionMulti-omics researchDownstream analysisCellular statesOmics datasetsAdversarial networkNeural networkProteomic profilingCorrelated featuresBiological informationOmics perspectiveDiverse datasetsFeature topologyDisease mechanismsCell embeddingData resourcesRelationship inference
2024
Application of Deep-learning Methods for Distinguishing Gamma-Ray Bursts from Fermi/GBM Time-tagged Event Data
Zhang P, Li B, Gui R, Xiong S, Zou Z, Wang X, Li X, Cai C, Zhao Y, Zhang Y, Xue W, Zheng C, Zhao H. Application of Deep-learning Methods for Distinguishing Gamma-Ray Bursts from Fermi/GBM Time-tagged Event Data. The Astrophysical Journal Supplement Series 2024, 272: 4. DOI: 10.3847/1538-4365/ad2de5.Peer-Reviewed Original ResearchGamma-ray burstsFollow-up observationsConvolutional neural networkDeep learning methodsFermi/Gamma-ray Burst MonitorCount mapsBlind searchInput samplesApplication of deep learning methodsSGR J1935Convolutional neural network modelNaI detectorAttention mechanism moduleGamma raysSample of data setsVisualization methodManually set thresholdsGrad-CAMNeural networkAccuracy of inspectionT-SNEEvent dataMechanism moduleBurstTarget search
2023
Efficient IoT Malware Detection Using Convolution Neural Network and View-Invariant Block
Nasim A, Zhao H, Javed M, Mehmood A. Efficient IoT Malware Detection Using Convolution Neural Network and View-Invariant Block. 2023, 00: 8-14. DOI: 10.1109/iske60036.2023.10481346.Peer-Reviewed Original ResearchIoT malware detectionMalware binary filesMalware detection frameworkGlobal contextual informationConvolutional neural networkView-invariant modelSequence of imagesOpen-source platformMalware detectionIoT devicesMalware attacksFeature aggregationEx-filtrationFeature mapsDetection frameworkBinary filesAblation studiesMultiple viewsView-invariantColor imagesSequential dataNeural networkContextual informationVisual dataMalware
2022
Garbage Image Classification Based on Improved Residual Neural Networks
Zhao L, Zhao H. Garbage Image Classification Based on Improved Residual Neural Networks. 2022, 00: 7-13. DOI: 10.1109/icicml57342.2022.10009851.Peer-Reviewed Original ResearchConvolutional block attention moduleClassification accuracyAttention mechanismImproved residual neural networkGarbage image classificationGarbage classification algorithmResidual neural networkGarbage imagesImage classificationResNet34 networkAttention moduleClassification performanceFeature informationNeural networkClassification algorithmsArtificial network modelNetwork modelTarget informationResNet34ClassificationNetworkGarbageInformationAlgorithmAccuracy
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