2023 - Research.com Computer Science in Canada Leader Award
2020 - Member of the National Academy of Engineering For innovative applications of signal processing to industrial and bioengineering problems.
1999 - IEEE Fellow For contributions to digital signal processing applications in television and medical imaging.
1999 - Fellow of the Royal Society of Canada Academy of Science
The Canadian Academy of Engineering
Her primary areas of investigation include Artificial intelligence, Computer vision, Pattern recognition, Algorithm and Image processing. Her study in Artificial intelligence concentrates on Pixel, Sparse approximation, Iterative reconstruction, Compressed sensing and Deep learning. Her study looks at the relationship between Computer vision and topics such as Interpolation, which overlap with Bilinear interpolation, Edge and Image scaling.
Rabab K. Ward interconnects Contextual image classification and Facial recognition system in the investigation of issues within Pattern recognition. Rabab K. Ward has researched Algorithm in several fields, including Transformation, Common Scrambling Algorithm, Mathematical optimization and Filter. Her Image processing research includes elements of Image quality, Tone mapping and Video image.
Her primary scientific interests are in Artificial intelligence, Computer vision, Pattern recognition, Algorithm and Speech recognition. Her study in Artificial intelligence focuses on Feature extraction, Wavelet, Data compression, Compressed sensing and Pixel. The Pattern recognition study combines topics in areas such as Contextual image classification, Image, Facial recognition system and Artificial neural network.
Rabab K. Ward combines subjects such as Transform coding and Mathematical optimization with her study of Algorithm. Her Speech recognition research integrates issues from Brain–computer interface and Electroencephalography. The study incorporates disciplines such as Motion estimation and Block-matching algorithm in addition to Motion compensation.
Rabab K. Ward spends much of her time researching Artificial intelligence, Pattern recognition, Computer vision, Deep learning and Compressed sensing. Rabab K. Ward usually deals with Artificial intelligence and limits it to topics linked to Machine learning and Field. Her work deals with themes such as Epileptic seizure, Epilepsy, Electroencephalography and Signal, which intersect with Pattern recognition.
Her research is interdisciplinary, bridging the disciplines of Perception and Computer vision. Her Compressed sensing study integrates concerns from other disciplines, such as Dynamic contrast-enhanced MRI, Solver, Data mining and Greedy algorithm. Her Iterative reconstruction research includes elements of Algorithm and Computed tomography.
Her scientific interests lie mostly in Artificial intelligence, Pattern recognition, Deep learning, Photoplethysmogram and Compressed sensing. Her Artificial intelligence study combines topics from a wide range of disciplines, such as Machine learning and Natural language processing. Her Pattern recognition research is multidisciplinary, incorporating elements of Epileptic seizure, Epilepsy, Electroencephalography and Image.
Her Electroencephalography research is multidisciplinary, relying on both Speech recognition and Scalp. Her Compressed sensing research integrates issues from Optimization problem, Solver and Data mining. Her Convolution study which covers Neural coding that intersects with Computer vision.
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A survey of signal processing algorithms in brain-computer interfaces based on electrical brain signals.
Ali Bashashati;Mehrdad Fatourechi;Rabab K Ward;Gary E Birch;Gary E Birch.
Journal of Neural Engineering (2007)
Deep sentence embedding using long short-term memory networks: analysis and application to information retrieval
Hamid Palangi;Li Deng;Yelong Shen;Jianfeng Gao.
IEEE Transactions on Audio, Speech, and Language Processing (2016)
EMG and EOG artifacts in brain computer interface systems: A survey
Mehrdad Fatourechi;Ali Bashashati;Rabab K. Ward;Gary E. Birch;Gary E. Birch.
Clinical Neurophysiology (2007)
Telomeres in the mouse have large inter-chromosomal variations in the number of T2AG3 repeats
J. M. J. M. Zijlmans;U. M. Martens;S. S. S. Poon;A. K. Raap.
Proceedings of the National Academy of Sciences of the United States of America (1997)
Image Fusion With Convolutional Sparse Representation
Yu Liu;Xun Chen;Rabab K. Ward;Z. Jane Wang.
IEEE Signal Processing Letters (2016)
Fast Image/Video Contrast Enhancement Based on Weighted Thresholded Histogram Equalization
Qing Wang;R.K. Ward.
IEEE Transactions on Consumer Electronics (2007)
Short telomeres on human chromosome 17p.
U. M. Martens;J. M. J. M. Zijlmans;S. S. S. Poon;S. S. S. Poon;W. Dragowska.
Nature Genetics (1998)
Learning Sparse Representations for Human Action Recognition
T. Guha;R. K. Ward.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2012)
Deep learning for pixel-level image fusion: Recent advances and future prospects
Yu Liu;Xun Chen;Xun Chen;Zengfu Wang;Z. Jane Wang.
Information Fusion (2018)
Telomere length measurements using digital fluorescence microscopy
Steven S.S. Poon;Uwe M. Martens;Rabab K. Ward;Peter M. Lansdorp;Peter M. Lansdorp.
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