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Neural tissue and brain interfacing CMOS devices - An introduction to state-of-the-art, current and future challenges., , , , , , , , and . ISCAS, page 1826-1829. IEEE, (2016)Effectiveness of Employing Multimodal Signals in Removing Artifacts from Neuronal Signals: An Empirical Analysis., , and . BI, volume 12241 of Lecture Notes in Computer Science, page 183-193. Springer, (2020)Towards a data-driven adaptive anomaly detection system for human activity., , and . Pattern Recognit. Lett., (2021)An event based topic learning pipeline for neuroimaging literature mining., , , , , and . Brain Informatics, 7 (1): 18 (2020)Enhancing biofeedback-driven self-guided virtual reality exposure therapy through arousal detection from multimodal data using machine learning., , , , , , , , , and 7 other author(s). Brain Informatics, 10 (1): 14 (December 2023)SANTIA: a Matlab-based open-source toolbox for artifact detection and removal from extracellular neuronal signals., , , , , , , , and . Brain Informatics, 8 (1): 14 (2021)Deep Learning in Mining Biological Data., , and . CoRR, (2020)A Non-Blind Watermarking Scheme for Gray Scale Images in Discrete Wavelet Transform Domain using Two Subbands, , , , and . CoRR, (2012)iReTADS: An Intelligent Real-Time Anomaly Detection System for Cloud Communications Using Temporal Data Summarization and Neural Network., , , , and . Secur. Commun. Networks, (2022)Detection and Classification of Leukocytes in Blood Smear Images: State of the Art and Challenges., , and . Int. J. Ambient Comput. Intell., 12 (2): 111-139 (2021)