模糊逻辑
计算机科学
面部表情
人工智能
深度学习
模式识别(心理学)
机器学习
作者
Anand Singh Rajawat,Pradeep Bedi,Shreyas Goyal,Pawan Bhaladhare,Alok Aggarwal,Ravi Shankar Singhal
标识
DOI:10.1016/j.procs.2023.01.251
摘要
One of the critical issues in detecting depression is using facial expressions with image data classification. In This research paper, we proposed Fusion Fuzzy Logic((FFL) with deep learning for identifying depressed people based on their facial expressions. Our proposed model the based on an advanced fuzzy algorithm with deep learning for unordered fuzzy rule(FR) initiation to offer appropriate and suitable opinions based on depressed people's facial expressions(FE), to allow Depression Recognition(DR) from image files and recorded video files. The primary goal of this research work was to use the fusion method to turn these facial expressions (FE) into the detection of depressed states. To elevate the performance of the Fusion Fuzzy Logic((FFL) (fuzzy logic and CNN)), delivering them entreated them several times to imitate specific facial expressions. Our proposed FFL with the CNN model produces exact and dependable results with a 94.3% overall accuracy comparable to human recognition.
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