What is he best known for?
The fields of study he is best known for:
- Electrical engineering
- Artificial intelligence
- Telecommunications
Rachid M. Alameh spends much of his time researching Electrical engineering, Computer hardware, Electronic engineering, Signal and Artificial intelligence.
The concepts of his Electrical engineering study are interwoven with issues in Mechanism and Wearable computer.
His research integrates issues of Wireless and Focus in his study of Computer hardware.
His study in Electronic engineering is interdisciplinary in nature, drawing from both Acoustics, Object and Mobile device.
As a part of the same scientific study, he usually deals with the Signal, concentrating on Proximity sensor and frequently concerns with Orientation.
His Artificial intelligence research is multidisciplinary, relying on both Microprocessor, Data management and Computer vision.
His most cited work include:
- Electronic device with sensing assembly and method for interpreting offset gestures (276 citations)
- Intuitive user interface and method (193 citations)
- Portable electronic device having directional proximity sensors based on device orientation (192 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Computer hardware, Electrical engineering, Electronic engineering, Signal and Artificial intelligence.
His Computer hardware research incorporates elements of Mode, Communication device, Transceiver and Wireless.
His Electrical engineering research is multidisciplinary, incorporating elements of Mechanism and Wearable computer.
Rachid M. Alameh focuses mostly in the field of Electronic engineering, narrowing it down to matters related to Acoustics and, in some cases, Hinge.
The Signal study combines topics in areas such as Proximity sensor, Infrared and Detector.
Rachid M. Alameh has researched Artificial intelligence in several fields, including Authentication, Control circuit and Computer vision.
He most often published in these fields:
- Computer hardware (24.62%)
- Electrical engineering (24.12%)
- Electronic engineering (22.11%)
What were the highlights of his more recent work (between 2018-2021)?
- Computer hardware (24.62%)
- Computer network (4.02%)
- Speech recognition (4.02%)
In recent papers he was focusing on the following fields of study:
Rachid M. Alameh mostly deals with Computer hardware, Computer network, Speech recognition, Direct voice input and Authentication.
His biological study spans a wide range of topics, including Mode, Limiting and Wearable computer.
His work deals with themes such as Image capture, Image, Computer vision and Artificial intelligence, which intersect with Mode.
His research investigates the link between Bootstrapping and topics such as Mobile telephony that cross with problems in Mobile device.
His research in Power sensor tackles topics such as Electronics which are related to areas like Signal.
As part of the same scientific family, Rachid M. Alameh usually focuses on Signal, concentrating on Wireless and intersecting with Output device.
Between 2018 and 2021, his most popular works were:
- Electronic Device with Voice-Synthesis and Corresponding Methods (3 citations)
- Dynamically loaded phrase spotting audio-front end (1 citations)
- Communication session modifications based on a proximity context (1 citations)
In his most recent research, the most cited papers focused on:
- Electrical engineering
- Telecommunications
- Artificial intelligence
His main research concerns Computer network, Authentication, Session, Computer hardware and Direct voice input.
His Computer network study integrates concerns from other disciplines, such as Wireless, Block cipher mode of operation and Electronics.
His Session study combines topics from a wide range of disciplines, such as Distance based, Mechanism, Adaptive video and Wearable computer.
By researching both Computer hardware and Set, Rachid M. Alameh produces research that crosses academic boundaries.
Rachid M. Alameh interconnects Watermark, Speech synthesis and Formatted text in the investigation of issues within Direct voice input.
The concepts of his Speech recognition study are interwoven with issues in Seclusion and Data retrieval.
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