E-LIB Suche - Ergebnisse für: Vidyaratne, Lasitha

1

An ensemble of convolution-based methods for fault detectio..:

, In: 2023 IEEE International Conference on Prognostics and Health Management (ICPHM),

Lee, Xian Yeow ; Kumar, Aman ; Vidyaratne, Lasitha... - p. 172-179 , 2023

Link: https://doi.org/10.1109/..

2

3D far-field Lidar sensing and computational modeling for h..:

Glandon, Alexandar ; Vidyaratne, Lasitha ; Dhar, Nibir...
Applied Optics. , 2023

Link: https://doi.org/10.1364/..

3

Multi-module-based CVAE to predict HVCM faults in the SNS a..:

Alanazi, Yasir ; Schram, Malachi ; Rajput, Kishansingh...
Machine Learning with Applications. 13 (2023) - p. 100484 , 2023

Link: https://doi.org/10.1016/..

4

XDNet: A Few-Shot Meta-Learning Approach for Cross-Domain V..:

, In: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW),

Lee, Xian Yeow ; Vidyaratne, Lasitha ; Alam, Mahbubul... - p. 4375-4384 , 2023

Link: https://doi.org/10.1109/..

5

Time series anomaly detection in power electronics signals ..:

Radaideh, Majdi I. ; Pappas, Chris ; Walden, Jared...
Digital Signal Processing. 130 (2022) - p. 103704 , 2022

Link: https://doi.org/10.1016/..

6

Deep Learning Based Superconducting Radio-Frequency Cavity ..:

Vidyaratne, Lasitha ; Carpenter, Adam ; Powers, Tom...
Frontiers in Artificial Intelligence. 4 (2022) - p. , 2022

Link: https://doi.org/10.3389/..

7

Brain Tumor Classification Using 3D Convolutional Neural Ne..:

, In: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries; Lecture Notes in Computer Science,

Pei, Linmin ; Vidyaratne, Lasitha ; Hsu, Wei-Wen.. - p. 335-342 , 2020

Link: https://doi.org/10.1007/..

8

Multimodal Brain Tumor Segmentation and Survival Prediction..:

, In: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries; Lecture Notes in Computer Science,

Pei, Linmin ; Vidyaratne, Lasitha ; Monibor Rahman, M... - p. 73-81 , 2020

Link: https://doi.org/10.1007/..

9

Context aware deep learning for brain tumor segmentation, s..:

Pei, Linmin ; Vidyaratne, Lasitha ; Rahman, Md Monibor.
Scientific Reports. 10 (2020) 1 - p. , 2020

Link: https://doi.org/10.1038/..

10

Superconducting radio-frequency cavity fault classification..:

Tennant, Chris ; Carpenter, Adam ; Powers, Tom...
Physical Review Accelerators and Beams. 23 (2020) 11 - p. , 2020

Link: https://doi.org/10.1103/..

11

Glioblastoma Survival Prediction:

, In: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries; Lecture Notes in Computer Science,

Shboul, Zeina A. ; Alam, Mahbubul ; Vidyaratne, Lasitha.. - p. 508-515 , 2019

Link: https://doi.org/10.1007/..

12

Feature-Guided Deep Radiomics for Glioblastoma Patient Surv..:

Shboul, Zeina A. ; Alam, Mahbubul ; Vidyaratne, Lasitha...
Frontiers in Neuroscience. 13 (2019) - p. , 2019

Link: https://doi.org/10.3389/..

13

An ensemble of convolution-based methods for fault detectio..:

Lee, Xian Yeow ; Kumar, Aman ; Vidyaratne, Lasitha...
http://arxiv.org/abs/2305.05532. , 2023

Link: http://arxiv.org/abs/230..

14

Multi-module based CVAE to predict HVCM faults in the SNS a..:

Alanazi, Yasir ; Schram, Malachi ; Rajput, Kishansingh...
http://arxiv.org/abs/2304.10639. , 2023

Link: http://arxiv.org/abs/230..

15

Deep Learning Based Superconducting Radio-Frequency Cavity ..:

Vidyaratne, Lasitha ; Carpenter, Adam ; Powers, Tom...
https://digitalcommons.odu.edu/ece_fac_pubs/304. , 2022

Link: https://digitalcommons.o..