What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Operating system
His main research concerns Speech recognition, Noise, Acoustics, Electronic engineering and Artificial intelligence.
His biological study spans a wide range of topics, including Artificial neural network and Speech enhancement, PESQ.
His Noise research integrates issues from Microphone array, Beamforming, Adaptive beamformer and Gaussian noise.
His work deals with themes such as Matching and Microphone, which intersect with Acoustics.
His Electronic engineering study integrates concerns from other disciplines, such as Sound quality, Automatic test equipment, Background noise and Multipath propagation.
Rafik Goubran has researched Artificial intelligence in several fields, including Signal, Computer vision and Pattern recognition.
His most cited work include:
- Robust voice activity detection using higher-order statistics in the LPC residual domain (203 citations)
- Speech quality prediction in VoIP using the extended E-model (126 citations)
- Integration of Smart Home Technologies in a Health Monitoring System for the Elderly (115 citations)
What are the main themes of his work throughout his whole career to date?
Rafik Goubran focuses on Speech recognition, Artificial intelligence, Acoustics, Signal and Electronic engineering.
His research integrates issues of Speech enhancement, Noise and Echo in his study of Speech recognition.
His Noise research is multidisciplinary, incorporating perspectives in Noise reduction and Background noise.
Rafik Goubran combines subjects such as Machine learning, Computer vision and Pattern recognition with his study of Artificial intelligence.
His Acoustics research incorporates themes from Microphone array, Microphone and Beamforming.
His Signal study combines topics from a wide range of disciplines, such as Simulation, Magnification and Breathing.
He most often published in these fields:
- Speech recognition (23.34%)
- Artificial intelligence (19.60%)
- Acoustics (14.70%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (19.60%)
- Pattern recognition (9.80%)
- Cognition (5.76%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Artificial intelligence, Pattern recognition, Cognition, Dementia and Cognitive health.
His work carried out in the field of Artificial intelligence brings together such families of science as Sleep apnea and Computer vision.
His study in Pattern recognition is interdisciplinary in nature, drawing from both Signal and Apnea.
His studies in Signal integrate themes in fields like Band-pass filter and Gaussian noise.
His Dementia research includes themes of Home automation and Physical medicine and rehabilitation.
His Event research is multidisciplinary, incorporating perspectives in Segmentation and Speech recognition.
Between 2017 and 2021, his most popular works were:
- Abnormality Detection in Mammography using Deep Convolutional Neural Networks (31 citations)
- Posture Detection Using Sounds and Temperature: LMS-Based Approach to Enable Sensory Substitution (11 citations)
- An integrated approach for medical abnormality detection using deep patch convolutional neural networks (10 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Operating system
His primary areas of study are Cognition, Artificial intelligence, Remote patient monitoring, Pattern recognition and Physical medicine and rehabilitation.
In general Cognition study, his work on Cognitive status often relates to the realm of Physical health, thereby connecting several areas of interest.
The Artificial intelligence study combines topics in areas such as Instrumentation, State, Sensory substitution, Computer vision and Measure.
His Remote patient monitoring research incorporates themes from Sleep monitoring, Bed Occupancy, Real-time computing and Sensor fusion.
His Pattern recognition study which covers Apnea that intersects with Support vector machine.
His research in Physical medicine and rehabilitation focuses on subjects like Longitudinal study, which are connected to Sleep.
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