| Type of Material: | Thesis |
| Title: | Innovative schemes for emotions recognition in human computer interaction using machine learning and fuzzy techniques |
| Researcher: | Goyal, Samta Jain |
| Guide: | Upadhyay, Arvind Kumar | Jadon, R S |
| Department: | Computer Science and Engineering |
| Publisher: | Amity University Madhya Pradesh |
| Place: | Gwalior |
| Year: | 2020 |
| Language: | English |
| Subject: | Machine Learning | Computer Science and Applications | Engineering and Technology |
| Dissertation/Thesis Note: | PhD; Computer Science and Engineering, Amity University Madhya Pradesh, Gwalior; 2020 |
| Fulltext: | Shodhganga |
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| 008 | __ | 260907t2020||||ii#||||g|m||||||||||eng|| |
| 035 | __ | |a(IN-AhILN)th_462760 |
| 040 | __ | |dIN-AhILN|aAMIT_474020 |
| 041 | __ | |aeng |
| 100 | __ | |eResearcher|aGoyal, Samta Jain |
| 110 | __ | |aComputer Science and Engineering|0U-0604|dGwalior|bAmity University Madhya Pradesh|ein |
| 245 | __ | |aInnovative schemes for emotions recognition in human computer interaction using machine learning and fuzzy techniques |
| 260 | __ | |aGwalior|c2020|bAmity University Madhya Pradesh |
| 300 | __ | |aVXii,157|dDVD |
| 502 | __ | |cComputer Science and Engineering, Amity University Madhya Pradesh, Gwalior|d2020|bPhD |
| 518 | __ | |oDate of Award|d2020 |
| 518 | __ | |d2014|oDate of Registration |
| 518 | __ | |oDate of Completion|d2020 |
| 520 | __ | |aOver the last decades, most studies have concentrated on emotional signals in facial expressions. Recently, researchers have also turned to emotional body language, i.e. the expression of emotions through the human body pose and/or body motion. An implicit assumption common to the work on emotional body language is that body language is only a different means of expressing the same set of basic emotions as facial expressions. The recognition of whole-body expressions is substantially harder, because the configuration of the human body has more degrees of freedom than the face alone, and its overall shape varies strongly during articulated motion. However, in computer vision and machine learning research, recent results about object recognition have shown that even for highly variable visual stimuli, quite reliable categorical decisions can be made from dense low-level visual cues.In this work, we try to gain new insight into possible mechanisms of emotion recognition from hand gestures. We believe that such |
| 650 | __ | |aComputer Science and Applications|2UGC |
| 650 | __ | |aEngineering and Technology|2AIU |
| 653 | __ | |aMachine Learning |
| 700 | __ | |aUpadhyay, Arvind Kumar|eGuide |
| 700 | __ | |aJadon, R S|eGuide |
| 856 | __ | |uhttp://shodhganga.inflibnet.ac.in/handle/10603/278898|yShodhganga |
| 905 | __ | |afromsg |
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