Algoritmi | User | Miguel Ângelo Peixoto da Costa


Miguel Ângelo Peixoto da Costa

Miguel Ângelo Peixoto da Costa
At LASI
Other with MSc
Member of the CALG R&D Unit
Academic Degree
MSc
Current Position
Other at Escola de Engenharia da Universidade do Minho
Personal Webpage
Personal Email
miguel.costa@dei.uminho.ptOrcid
0000-0003-2046-4569Researcher ID
FCT Public Key
J8127805LhJX
Ciência ID
Google Scholar
About Me
Miguel Costa is a Ph.D. student of Electronics and Computer Engineering at the University of Minho, Portugal. From this same institution, Miguel received an M.Sc. also in this academic topic, with a special focus on embedded systems and information systems and technologies. During his Master’s, Miguel was invited to enroll in an R&D project, InnovCar, where he addressed the development of an AI-based driver monitoring system. After ending his Master’s, Miguel joined the R&D project MOG WALLSCREEN, where he was responsible for developing a memory manager, in reconfigurable hardware, for a video card supporting 8k resolution, along with an API to control the board. His main research interests include machine learning, reconfigurable computing (FPGA technology) and real-time systems.
Publications (6)
SecureQNN: Introducing a Privacy-Preserving Framework for QNNs at the Deep Edge
2023 | book-chapter
Shifting Capsule Networks from the Cloud to the Deep Edge
ACM Transactions on Intelligent Systems and Technology
2022 | journal-article
Train Me If You Can: Decentralized Learning on the Deep Edge
Applied Sciences
2022 | journal-article
Wall Screen: An Ultra-High Definition Video-Card for the Internet of Things
IEEE MultiMedia
2020 | journal-article
The Future of Low-End Motes in the Internet of Things: A Prospective Paper
Electronics
2020 | journal-article
Detecting Driver’s Fatigue, Distraction and Activity Using a Non-Intrusive Ai-Based Monitoring System
Journal of Artificial Intelligence and Soft Computing Research
2019 | journal-article
SecureQNN: Introducing a Privacy-Preserving Framework for QNNs at the Deep Edge
2023 | book-chapter
Shifting Capsule Networks from the Cloud to the Deep Edge
ACM Transactions on Intelligent Systems and Technology
2022 | journal-article
Train Me If You Can: Decentralized Learning on the Deep Edge
Applied Sciences
2022 | journal-article
Wall Screen: An Ultra-High Definition Video-Card for the Internet of Things
IEEE MultiMedia
2020 | journal-article
The Future of Low-End Motes in the Internet of Things: A Prospective Paper
Electronics
2020 | journal-article
Detecting Driver’s Fatigue, Distraction and Activity Using a Non-Intrusive Ai-Based Monitoring System
Journal of Artificial Intelligence and Soft Computing Research
2019 | journal-article