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Feature selection and classification of oil spills in SAR image based on statistics and artificial neural network., , , , и . IGARSS, стр. 569-571. IEEE, (2014)Integration of Handcrafted and Embedded Features from Functional Connectivity Network with rs-fMRI forBrain Disease Classification., , , , , и . MLMI@MICCAI, том 12966 из Lecture Notes in Computer Science, стр. 674-681. Springer, (2021)Integrated Registration and Occlusion Handling Based on Deep Learning for Augmented-Reality-Assisted Assembly Instruction., , , , и . IEEE Trans. Ind. Informatics, 19 (5): 6825-6835 (мая 2023)An adaptive threshod segmentation algorithm to extract dark targets from SAR images., , , и . IGARSS, стр. 1765-1768. IEEE, (2014)Constructing High-Order Dynamic Functional Connectivity Networks from Resting-State fMRI for Brain Dementia Identification., , , , и . MLMI@MICCAI, том 12436 из Lecture Notes in Computer Science, стр. 303-311. Springer, (2020)Novel learning framework for optimal multi-object video trajectory tracking., , , , и . Virtual Real. Intell. Hardw., 5 (5): 422-438 (октября 2023)Extracting Sequential Features from Dynamic Connectivity Network with rs-fMRI Data for AD Classification., , , , , и . MLMI@MICCAI, том 12966 из Lecture Notes in Computer Science, стр. 664-673. Springer, (2021)An adversarial sample detection method based on heterogeneous denoising., , , , , и . Mach. Vis. Appl., 35 (4): 96 (июля 2024)An Efficient and Secure Itinerary-Based Data Aggregation Algorithm for WSNs., , , , и . TrustCom/BigDataSE/ICESS, стр. 433-440. IEEE Computer Society, (2017)