Autumn School CICESE VI – El Mexicano

ENSENADA- With a view to engaging students from higher education institutions pursuing careers related to computer science in research activities, November 8-12, Sixth Autumn School in Computer Science organized by CICESE in a virtual format.

This activity, in addition to the foregoing, also seeks to introduce the graduate programs and lines of research bred in the Department of Computer Science at CICESE, and to encourage students to pursue a postgraduate degree with a scientific career.

The sixth edition of this school in computer science added the participation of 20 engineering students in computing, computer systems, software, robotics, mechatronics, electronics and a degree in physical and mathematical sciences, attached to universities, public technology and private bodies of eleven entities: Baja California, Mexico City, State of Mexico, Jalisco, Michoacan, Oaxaca, Puebla, Sinaloa, Sonora, Veracruz and Zacatecas.

During these days, participants were part of a program of seven talks by CICESE researchers on topics representative of the department’s research groups, four workshops given by researchers and graduate students, and a student meeting; All activities focused on learning about the latest science on frontier issues and experimenting with current problems and techniques in different areas of computer science.

Welcoming the event was responsible Gilberto Lopez Mariscal, Postgraduate Coordinator in the area, who noted that this program started in the Department of Computer Science in 2000, belongs to CONASET’s National Graduate Program for Quality (Standard Level) and has a number of students currently enrolled 37 students (27 Masters and 10 Ph.D.) and 388 graduates (331 Masters and 57 Ph.D.). At the short ceremony, Dr. Ana Isabel Martinez, Head of the Department of Computer Science, added her welcome message.

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During the Faculty of Computational Sciences, Dr. Hugo Hidalgo Silva, a researcher at CICESE, shared the topic “Neural Networks and Filters in Images” which raises the profile of these networks as a filtering technique within an algorithm for general image recovery.

“This technology has applications in all areas where there are problems for retrieving information in the form of images, obtained through signals outside the subject of the study, that is, it can be applied to medical tomography, seismic tomography and modeling in the Earth sciences, among others.”

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