Projects per year
Organisation profile
Organisation profile
‧Degree Program The school's degree programs consist of the master's degree program and the doctoral degree program. The bachelor's degree program will be appended in the future according to actual needs, so will the faculty recruitment and the number of students. The concept of the degree programs is to provide an environment for students to develop scientific knowledge, computing skills, and soft power. Besides learning the theoretical knowledge and practical skills of basic computing and professional disciplines, students also build up soft power capabilities such as social care, issue analysis, communication and cooperation, innovative applications, and system integration. Only with the combination of rational professional knowledge, emotional, social care, and the ability to integrate interdisciplinary systems can we realize the vision of "using applied computing technology to improve social well-being. ‧Credit Program The goal of the credit programs is to instruct the students of various disciplines (non-computing-related) to enhance their computing knowledge, skills, and tools based on the applicant's actual professional knowledge through an application-oriented teaching model interdisciplinary faculties, helping them to solve problems and enhance their self-worth. Students who have completed the credit programs may then return to their original departments, introduce their computing knowledge and skills into integrated applications, or transfer into the (master's and doctoral) degree programs if they choose to. Interdisciplinary credit programs consist of preparatory and core computing technology courses, combined with advanced courses in different disciplines.Fingerprint
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Collaborations and top research areas from the last five years
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Profiles
Projects
- 1 Finished
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Internet-of-Things-based Multi-sensor Structure for Geriatric Healthcare
Ni, J. C., Yang, C. S., Shiu, L. C. & Wu, M. Y., 2023, In: Sensors and Materials. 35, 3, p. 1131-1140 10 p.Research output: Contribution to journal › Article › peer-review
Open Access -
Involvement of Deep Learning for Vision Sensor-Based Autonomous Driving Control: A Review
Khanum, A., Lee, C. Y. & Yang, C. S., 2023 Jul 15, In: IEEE Sensors Journal. 23, 14, p. 15321-15341 21 p.Research output: Contribution to journal › Article › peer-review
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Lightweight Authentication Mechanism for Industrial IoT Environment Combining Elliptic Curve Cryptography and Trusted Token
Yang, Y. S., Lee, S. H., Wang, J. M., Yang, C. S., Huang, Y. M. & Hou, T. W., 2023 May, In: Sensors. 23, 10, 4970.Research output: Contribution to journal › Article › peer-review
Open Access2 Citations (Scopus)