Artículos de revistas

URI permanente para esta colecciónhttps://hdl.handle.net/20.500.12640/4067

Examinar

Seleccione resultados tecleando las primeras letras
Mostrando 1 - 2 de 2
  • Miniatura
    ÍtemAcceso Abierto
    Detección del estado fisiológico de los ojos en conductores mediante técnicas de visión artificial
    (Universidad de Tarapacá, 2019-12-01) Ale Ale, Neisser; Fabián, Junior
    In recent decades, the number of traffic accidents due to fatigue or drowsiness of the driver has caused significant human and material losses. At the same time, the sale in the vehicle fleet has been massified, which indicates thatpossibly in the following years, if the pertinent measures are not taken to detect fatigue, there will be an increase in automobile accidents. Therefore, in this research study, the development of a fatigue detection system in drivers that allows alerting about their status while driving using artificial vision and machine learning techniques is proposed. The techniques of these two fields of study are intercepted to generate supervised models with high performance when classifying the state of fatigue in drivers. In this study, a dataset of frontal images focusing on the physiological characteristics of the eyes was used; obtaining promising preliminary results in the detection of fatigue in real-time.
  • Miniatura
    ÍtemAcceso Abierto
    DruBot: prototipo robótico para autenticación por comparación de proporciones faciales para el control de asistencia y detectar la suplantación en evaluaciones
    (Universidad Nacional de Ingeniería, 2019-06-06) Ale Ale, Neisser; Huisacayna Cutipa, Abigail; Yallico Arias, Tereza; Calderón Niquín, Marks
    The work ‘DruBot: Robotic prototype for authentication and comparison of facial proportions for assistance control and impersonation detection in evaluations’ describes the development of the robotic prototype called DruBot that seeks to recognize the faces of the persons who join to a classroom specific, a private area or an examination, comparing them with a database for eachcase (to distinguish them from the characteristics extracted from the photo of the university identification and the frames obtained of the video of welcome of every student) and to determine if the image of the person which camera is capturing has or hasn’t access to the area, issuing a different sign if his or her access is allowed or not. We apply technologies of artificial vision (Haar cascade for the detection of faces in the whole image captured by camera in real time and Face Landmarks to find the key points of human detected face, to calculate his proportions with Euclidean distances and to compare for the recognition of every person in specific) and serial communication with electronic devices so that the presents notice when there is an intruder or when the student has been recognized well and register his or her assistance.