What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
Rajeev Sharma mainly investigates Artificial intelligence, Human–computer interaction, Gesture recognition, Interface and Gesture.
He combines subjects such as Computer vision and Pattern recognition with his study of Artificial intelligence.
In the field of Computer vision, his study on Face model, Projection and Augmented reality overlaps with subjects such as Set and Demographics.
His Pattern recognition study combines topics in areas such as Optical flow and Facial expression.
The study incorporates disciplines such as Modality, Visual computing and Virtual reality in addition to Gesture recognition.
In his works, Rajeev Sharma performs multidisciplinary study on Gesture and Process.
His most cited work include:
- Visual interpretation of hand gestures for human-computer interaction: a review (1871 citations)
- Toward multimodal human-computer interface (256 citations)
- Recognition of facial expressions and measurement of levels of interest from video (202 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Artificial intelligence, Computer vision, Robot, Human–computer interaction and Gesture.
His Artificial intelligence research is multidisciplinary, incorporating elements of Machine learning and Pattern recognition.
His study in Computer vision is interdisciplinary in nature, drawing from both Robot control and Motion control.
In the subject of general Robot, his work in Motion planning and Robotics is often linked to Coding, thereby combining diverse domains of study.
The Gesture recognition research Rajeev Sharma does as part of his general Gesture study is frequently linked to other disciplines of science, such as Deixis and Set, therefore creating a link between diverse domains of science.
His study explores the link between Gesture recognition and topics such as Natural language processing that cross with problems in Prosody.
He most often published in these fields:
- Artificial intelligence (59.60%)
- Computer vision (43.43%)
- Robot (22.22%)
What were the highlights of his more recent work (between 2005-2020)?
- Microbiology (2.02%)
- Pasteurella multocida (2.02%)
- Geospatial analysis (8.08%)
In recent papers he was focusing on the following fields of study:
Microbiology, Pasteurella multocida, Geospatial analysis, Crisis management and Isolation are his primary areas of study.
His research in the fields of Typing overlaps with other disciplines such as Filamentous haemagglutinin adhesin.
Pasteurella multocida combines with fields such as Biochemistry, Bacterial outer membrane, Polyacrylamide gel electrophoresis, Pasteurella multocida serotype and Extraction in his investigation.
His Geospatial analysis study spans across into subjects like Emergency management, Relevance, Human–computer interaction, Immediacy and Risk management.
Crisis management is integrated with Geovisualization, Process management, Mobile device, Analytics and Information access in his research.
Rajeev Sharma performs integrative study on Isolation and Molecular identification in his works.
Between 2005 and 2020, his most popular works were:
- Recognition of facial expressions and measurement of levels of interest from video (202 citations)
- Human-GIS interaction issues in crisis response (26 citations)
- GeoCollaborative crisis management: designing technologies to meet real-world needs (21 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Machine learning
His primary areas of investigation include Crisis management, Geospatial analysis, Speech recognition, Linear classifier and Face detection.
He integrates many fields in his works, including Crisis management, Geovisualization, Risk management, Immediacy, Human–computer interaction and Relevance.
Along with Geospatial analysis, other disciplines of study including Emergency management, Knowledge management, User-centered design, Work and Interoperability are integrated into his research.
His Speech recognition study integrates concerns from other disciplines, such as Optical flow, Facial recognition system and Facial expression.
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