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dc.contributor.authorBhatt, Priya
dc.contributor.authorSethi, Amanrose
dc.contributor.authorTasgaonkar, Vaibhav
dc.contributor.authorShroff, Jugal
dc.contributor.authorPendharkar, Isha
dc.contributor.authorDesai, Aditya
dc.contributor.authorSinha, Pratyush
dc.contributor.authorDeshpande, Aditya
dc.contributor.authorJoshi, Gargi
dc.contributor.authorRahate, Anil
dc.contributor.authorJain, Priyanka
dc.contributor.authorWalambe, Rahee
dc.contributor.authorKotecha, Ketan
dc.contributor.authorJain, N. K.
dc.date.accessioned2023-12-15T09:26:45Z
dc.date.available2023-12-15T09:26:45Z
dc.date.issued2023
dc.identifier.issn10.1186/s40708-023-00196-6
dc.identifier.urihttps://thuvienso.hoasen.edu.vn/handle/123456789/14627
dc.descriptionpp: 01 -37.vi
dc.description.abstractHuman behaviour reflects cognitive abilities. Human cognition is fundamentally linked to the different experiences or characteristics of consciousness/emotions, such as joy, grief, anger, etc., which assists in effective communication with others. Detection and differentiation between thoughts, feelings, and behaviours are paramount in learning to control our emotions and respond more effectively in stressful circumstances. The ability to perceive, analyse, process, interpret, remember, and retrieve information while making judgments to respond correctly is referred to as Cognitive Behavior. After making a significant mark in emotion analysis, deception detection is one of the key areas to connect human behaviour, mainly in the forensic domain. Detection of lies, deception, malicious intent, abnormal behaviour, emotions, stress, etc., have significant roles in advanced stages of behavioral science. Artificial Intelligence and Machine learning (AI/ML) has helped a great deal in pattern recognition, data extraction and analysis, and interpretations. The goal of using AI and ML in behavioral sciences is to infer human behaviour, mainly for mental health or forensic investigations. The presented work provides an extensive review of the research on cognitive behaviour analysis. A parametric study is presented based on different physical characteristics, emotional behaviours, data collection sensing mechanisms, unimodal and multimodal datasets, modelling AI/ML methods, challenges, and future research directions.vi
dc.language.isoenvi
dc.publisherSpinger Openvi
dc.subjectCognitive behavior analysisvi
dc.subjectMultimodal AIvi
dc.subjectMultimodal data fusionvi
dc.subjectAffective computingvi
dc.subjectBrain-inspired AIvi
dc.subjectDeception detectionvi
dc.titleMachine learning for cognitive behavioral analysis: datasets, methods, paradigms, and research directionsvi
dc.typeWorking Papervi


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