What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Computer vision
Ryosuke Shibasaki mostly deals with Artificial intelligence, Computer vision, Global Positioning System, Coordinate system and Remote sensing.
He interconnects Machine learning, Line and Computer graphics in the investigation of issues within Artificial intelligence.
His research in Computer vision intersects with topics in Range and Laser, Laser scanning.
His Multipath mitigation and GNSS applications study, which is part of a larger body of work in Global Positioning System, is frequently linked to Emergency management, bridging the gap between disciplines.
His work carried out in the field of Coordinate system brings together such families of science as Odometer, Acceleration, Gravity, Assisted GPS and Motion capture.
The study incorporates disciplines such as Extraction, Semi automatic and Satellite image in addition to Remote sensing.
His most cited work include:
- Activity-aware map: identifying human daily activity pattern using mobile phone data (217 citations)
- A novel system for tracking pedestrians using multiple single-row laser-range scanners (206 citations)
- Global estimation of crop productivity and the impacts of global warming by GIS and EPIC integration (182 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Global Positioning System, Remote sensing and Data mining.
He has included themes like Machine learning and Pattern recognition in his Artificial intelligence study.
His Computer vision research is multidisciplinary, relying on both Range, Computer graphics and Laser, Laser scanning.
The concepts of his Global Positioning System study are interwoven with issues in Real-time computing, Simulation and Mobile phone.
He most often published in these fields:
- Artificial intelligence (34.38%)
- Computer vision (22.85%)
- Global Positioning System (13.48%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (34.38%)
- Deep learning (6.45%)
- Big data (4.30%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Artificial intelligence, Deep learning, Big data, Global Positioning System and Data science.
His Artificial intelligence study combines topics from a wide range of disciplines, such as Machine learning, Recommender system, Computer vision and Pattern recognition.
Search engine is closely connected to Public service in his research, which is encompassed under the umbrella topic of Deep learning.
The Big data study combines topics in areas such as Database transaction and Environmental resource management.
His Global Positioning System research incorporates themes from Computation, Transport engineering, Data mining and Mobile phone.
His research in Data science focuses on subjects like Urban planning, which are connected to Categorization.
Between 2018 and 2021, his most popular works were:
- GPS data in urban online ride-hailing: A comparative analysis on fuel consumption and emissions (25 citations)
- DeepUrbanEvent: A System for Predicting Citywide Crowd Dynamics at Big Events (22 citations)
- Measuring spatio-temporal accessibility to emergency medical services through big GPS data. (21 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Computer vision
Ryosuke Shibasaki spends much of his time researching Global Positioning System, Mobile phone, Artificial intelligence, Data science and Transport engineering.
Ryosuke Shibasaki interconnects Topic model, Latent Dirichlet allocation, Urban planning, Estimation and Big data in the investigation of issues within Global Positioning System.
Ryosuke Shibasaki has researched Mobile phone in several fields, including Distributed computing, Public transport, Reduction, Real-time computing and Trend line.
The various areas that Ryosuke Shibasaki examines in his Artificial intelligence study include Land cover and Pattern recognition.
His Data science research includes themes of Frame and Benchmark.
His Transport engineering research includes elements of Mode and Fuel efficiency.
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