What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Operating system
- The Internet
Human–computer interaction, Computer graphics, Augmented reality, Multimedia and Computer vision are his primary areas of study.
His Human–computer interaction research includes elements of Graphical user interface and User interface.
Jun Rekimoto has included themes like Ambient intelligence, Calm computing, Shape display and Lumen in his Computer graphics study.
His research in Augmented reality focuses on subjects like Object, which are connected to Computer-mediated reality, Ubiquitous computing, Wearable technology, Virtual reality and Image registration.
His Multimedia study integrates concerns from other disciplines, such as Workspace, Desktop metaphor and Information visualization.
His Computer vision research incorporates elements of Dielectric antennas, Antenna, Surface and Artificial intelligence.
His most cited work include:
- SmartSkin: an infrastructure for freehand manipulation on interactive surfaces (949 citations)
- Augmented surfaces: a spatially continuous work space for hybrid computing environments (663 citations)
- Pick-and-drop: a direct manipulation technique for multiple computer environments (640 citations)
What are the main themes of his work throughout his whole career to date?
Jun Rekimoto mainly investigates Human–computer interaction, Artificial intelligence, Computer vision, Multimedia and Wearable computer.
His study on Augmented reality is often connected to Field as part of broader study in Human–computer interaction.
His Augmented reality study frequently draws connections to other fields, such as Object.
His Computer vision study combines topics from a wide range of disciplines, such as Robot, Computer graphics and Position.
He combines subjects such as Laser and Virtual reality with his study of Computer graphics.
His research on User interface often connects related areas such as Ubiquitous computing.
He most often published in these fields:
- Human–computer interaction (27.91%)
- Artificial intelligence (25.58%)
- Computer vision (23.64%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (25.58%)
- Human–computer interaction (27.91%)
- Computer vision (23.64%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Artificial intelligence, Human–computer interaction, Computer vision, Virtual reality and Artificial neural network.
His study in the fields of Pose under the domain of Artificial intelligence overlaps with other disciplines such as Field.
Jun Rekimoto integrates Human–computer interaction and Ideation in his research.
Jun Rekimoto interconnects Synchronizing and Angle of view in the investigation of issues within Computer vision.
His study looks at the intersection of Process and topics like Gesture with Wearable computer.
His research investigates the link between Mixed reality and topics such as Projection that cross with problems in Computer graphics.
Between 2018 and 2021, his most popular works were:
- SottoVoce: An Ultrasound Imaging-Based Silent Speech Interaction Using Deep Neural Networks (25 citations)
- ElasticVR: Providing Multilevel Continuously-Changing Resistive Force and Instant Impact Using Elasticity for VR (13 citations)
- Bubble: Wearable Assistive Grasping Augmentation Based on Soft Inflatables (5 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- The Internet
The scientist’s investigation covers issues in Artificial intelligence, Artificial neural network, Human–computer interaction, Machine learning and Simulation.
His Artificial intelligence research integrates issues from Synchronizing, Ball, Time perception and Computer vision.
His study in Artificial neural network is interdisciplinary in nature, drawing from both Speech interaction and Utterance.
Jun Rekimoto performs integrative study on Human–computer interaction and Musical composition.
His Machine learning study combines topics in areas such as User interface, Pose and Training.
His Simulation research is multidisciplinary, relying on both Vibration, Line, String and Sensation.
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