scholarly journals Automatic Lesser Kestrel’s Gender Identification using Video Processing

2017 ◽  
Author(s):  
Javier M. Mora-Merchan ◽  
Enrique Personal ◽  
Diego Francisco Larios ◽  
Francisco Javier Molina ◽  
Juan Carlos Tejero ◽  
...  
Keyword(s):  
Video Processing ◽  
Gender Identification

Perceptual Evaluation of Speech Naturalness in Speakers of Varying Gender Identities

2020 ◽  
Vol 63 (7) ◽  
pp. 2054-2069
Author(s):  
Brandon Merritt ◽  
Tessa Bent
Keyword(s):  
Spontaneous Speech ◽  
Identification Accuracy ◽  
Rating Task ◽  
Gender Identification ◽  
Identification Task ◽  
Male And Female ◽  
Perceptual Evaluation ◽  
Speech Training ◽  
And Gender ◽  
Speech Naturalness

Purpose The purpose of this study was to investigate how speech naturalness relates to masculinity–femininity and gender identification (accuracy and reaction time) for cisgender male and female speakers as well as transmasculine and transfeminine speakers. Method Stimuli included spontaneous speech samples from 20 speakers who are transgender (10 transmasculine and 10 transfeminine) and 20 speakers who are cisgender (10 male and 10 female). Fifty-two listeners completed three tasks: a two-alternative forced-choice gender identification task, a speech naturalness rating task, and a masculinity/femininity rating task. Results Transfeminine and transmasculine speakers were rated as significantly less natural sounding than cisgender speakers. Speakers rated as less natural took longer to identify and were identified less accurately in the gender identification task; furthermore, they were rated as less prototypically masculine/feminine. Conclusions Perceptual speech naturalness for both transfeminine and transmasculine speakers is strongly associated with gender cues in spontaneous speech. Training to align a speaker's voice with their gender identity may concurrently improve perceptual speech naturalness. Supplemental Material https://doi.org/10.23641/asha.12543158

Modern Technology for Image processing and Computer vision -A Review

2018 ◽  
Vol 1 (2) ◽  
pp. 17-23
Author(s):  
Takialddin Al Smadi
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Augmented Reality ◽  
Video Compression ◽  
Video Processing ◽  
Vision System ◽  
Citrus Fruit ◽  
Modern Technology ◽  
Image And Video Processing ◽  
Depth Video

This survey outlines the use of computer vision in Image and video processing in multidisciplinary applications; either in academia or industry, which are active in this field.The scope of this paper covers the theoretical and practical aspects in image and video processing in addition of computer vision, from essential research to evolution of application.In this paper a various subjects of image processing and computer vision will be demonstrated ,these subjects are spanned from the evolution of mobile augmented reality (MAR) applications, to augmented reality under 3D modeling and real time depth imaging, video processing algorithms will be discussed to get higher depth video compression, beside that in the field of mobile platform an automatic computer vision system for citrus fruit has been implemented ,where the Bayesian classification with Boundary Growing to detect the text in the video scene. Also the paper illustrates the usability of the handed interactive method to the portable projector based on augmented reality.   © 2018 JASET, International Scholars and Researchers Association

Classification of Esophageal and Bolus Movements for Evaluation of Swallowing Function by Ultrasound Video Processing Using Optical Flow and Stable Extremal Region Method

2019 ◽  
Vol 139 (5) ◽  
pp. 603-608 ◽  
Author(s):  
Yutaka Suzuki ◽  
Kyosuke Hatsushika ◽  
Keisuke Masuyama ◽  
Osamu Sakata ◽  
Morimasa Tanimoto ◽  
...  
Keyword(s):  
Optical Flow ◽  
Video Processing ◽  
Swallowing Function ◽  
Region Method

VIDEO PROCESSING IN VISUAL SYSTEM FOR COLOR DETECTION FOR PEOPLE WITH TRITANOPIA

2018 ◽  
Vol 7 (3) ◽  
pp. 17
Author(s):  
A. PENDHARI NAZNEEN ◽  
R. SEDAMKAR RAGHAVENDRA ◽  
◽  
Keyword(s):  
Visual System ◽  
Video Processing ◽  
Color Detection

scholarly journals Smart Care Using a DNN-Based Approach for Activities of Daily Living (ADL) Recognition

2020 ◽  
Vol 11 (1) ◽  
pp. 10
Author(s):  
Muchun Su ◽  
Diana Wahyu Hayati ◽  
Shaowu Tseng ◽  
Jiehhaur Chen ◽  
Hsihsien Wei
Keyword(s):  
Neural Network ◽  
Health Care ◽  
Activities Of Daily Living ◽  
Video Processing ◽  
Daily Living ◽  
Deep Neural Network ◽  
Recognition System ◽  
Automatic Recognition ◽  
Data Filtering ◽  
Accuracy Rate

Health care for independently living elders is more important than ever. Automatic recognition of their Activities of Daily Living (ADL) is the first step to solving the health care issues faced by seniors in an efficient way. The paper describes a Deep Neural Network (DNN)-based recognition system aimed at facilitating smart care, which combines ADL recognition, image/video processing, movement calculation, and DNN. An algorithm is developed for processing skeletal data, filtering noise, and pattern recognition for identification of the 10 most common ADL including standing, bending, squatting, sitting, eating, hand holding, hand raising, sitting plus drinking, standing plus drinking, and falling. The evaluation results show that this DNN-based system is suitable method for dealing with ADL recognition with an accuracy rate of over 95%. The findings support the feasibility of this system that is efficient enough for both practical and academic applications.

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