Electrical and Computer Engineering

Fingerprint Dive into the research topics where Electrical and Computer Engineering is active. These topic labels come from the works of this organization's members. Together they form a unique fingerprint.

Controllers Engineering & Materials Science
Feedback Engineering & Materials Science
Nonlinear systems Engineering & Materials Science
Millimeter waves Engineering & Materials Science
Switches Engineering & Materials Science
Antennas Engineering & Materials Science
Communication Engineering & Materials Science
Stabilization Engineering & Materials Science

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Profiles

No photo of H. Jonathan Chao
19802019
No photo of Anna Choromanska
20122019
No photo of Dariusz Czarkowski
19902019

Research Output 1968 2019

11.2 A CMOS Biosensor Array with 1024 3-Electrode Voltammetry Pixels and 93dB Dynamic Range

Manickam, A., You, K. D., Wood, N., Pei, L., Liu, Y., Singh, R., Gamini, N., Shahrjerdi, D., Kuimelis, R. G. & Hassibi, A., Mar 6 2019, 2019 IEEE International Solid-State Circuits Conference, ISSCC 2019. Institute of Electrical and Electronics Engineers Inc., p. 192-194 3 p. 8662507. (Digest of Technical Papers - IEEE International Solid-State Circuits Conference; vol. 2019-February).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Voltammetry
Biosensors
Pixels
Electrodes
Chemical stability

3D Point Cloud Denoising via Deep Neural Network Based Local Surface Estimation

Duan, C., Chen, S. & Kovacevic, J., May 1 2019, 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., p. 8553-8557 5 p. 8682812. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; vol. 2019-May).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Neural networks
Deep neural networks
Experiments
Deep learning

A damage localization and quantification algorithm for indirect structural health monitoring of bridges using multi-task learning

Liu, J., Bergés, M., Bielak, J., Garrett, J. H., Kovacevic, J. & Noh, H. Y., May 8 2019, 45th Annual Review of Progress in Quantitative Nondestructive Evaluation, Volume 38. Laflamme, S., Holland, S. & Bond, L. J. (eds.). American Institute of Physics Inc., 090003. (AIP Conference Proceedings; vol. 2102).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Open Access
health monitoring
structural health monitoring
learning
damage
monitoring