Hybrid Depression Detection Framework by Abdul Hamid (4 results)

Taschenbuch. Condition: Neu. Hybrid Depression Detection Framework Using BILSTM | Detection and Diagnosis | Danniel Shazmeer Bin Abdul Hamid (u. a.) | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786203200393 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Nowadays, due to mental stress, a significant section of society is affected by depression. There may be several reasons for depression, especially in adults. As a different person has different symptoms, and its identification is a significant challenge. Most people feel shy to accept that they are suffering from depression, while others are unaware of their depressed mental health. The objective of this work is to design and develop a practical tool or model to diagnose depression. In this work, a hybrid system is designed and simulated for detecting depression using EEG features, and facial features as a biological feature give an accurate diagnosis. EEG (Electroencephalogram) is the most adaptive way that can reflect the actual mental state among all biological signals. 84 pp. Englisch.…

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Bin Abdul Hamid Danniel ShazmeerMy name is Danniel Shazmeer. I had completed my Master in Information Technology at City University of Malaysia. I enjoy meeting new people and finding ways to help them have an uplifting experience. I.…

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Nowadays, due to mental stress, a significant section of society is affected by depression. There may be several reasons for depression, especially in adults. As a different person has different symptoms, and its identification is a significant challenge. Most people feel shy to accept that they are suffering from depression, while others are unaware of their depressed mental health. The objective of this work is to design and develop a practical tool or model to diagnose depression. In this work, a hybrid system is designed and simulated for detecting depression using EEG features, and facial features as a biological feature give an accurate diagnosis. EEG (Electroencephalogram) is the most adaptive way that can reflect the actual mental state among all biological signals.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 84 pp. Englisch. …