What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Algorithm
Ko Nishino mainly investigates Artificial intelligence, Computer vision, Reflectivity, Diffuse reflection and Specular reflection.
Artificial intelligence is often connected to Pattern recognition in his work.
His research integrates issues of Geometric data analysis and Robustness in his study of Computer vision.
The various areas that Ko Nishino examines in his Reflectivity study include Video tracking, Object detection, Shadow and Interpolation.
His work carried out in the field of Diffuse reflection brings together such families of science as Photometric stereo, Geometric modeling, Polarization, Texture mapping and Real image.
In his study, Surface is inextricably linked to Representation, which falls within the broad field of Object.
His most cited work include:
- Anomaly detection in extremely crowded scenes using spatio-temporal motion pattern models (526 citations)
- Bayesian Defogging (297 citations)
- Factorizing Scene Albedo and Depth from a Single Foggy Image (220 citations)
What are the main themes of his work throughout his whole career to date?
Ko Nishino mainly focuses on Artificial intelligence, Computer vision, Reflectivity, Surface and Real image.
Ko Nishino combines subjects such as Computer graphics and Pattern recognition with his study of Artificial intelligence.
The concepts of his Computer vision study are interwoven with issues in Specular reflection, Catadioptric system and Geometric modeling.
His work in the fields of Reflectivity, such as Photometric stereo, intersects with other areas such as Natural illumination and Field.
His Surface study integrates concerns from other disciplines, such as Sharpening, Multispectral image, Absorption, Active appearance model and Spectral power distribution.
While the research belongs to areas of Real image, Ko Nishino spends his time largely on the problem of Algorithm, intersecting his research to questions surrounding Artificial neural network, Point cloud and Pose.
He most often published in these fields:
- Artificial intelligence (83.59%)
- Computer vision (71.09%)
- Reflectivity (19.53%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (83.59%)
- Computer vision (71.09%)
- Representation (9.38%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Artificial intelligence, Computer vision, Representation, Real image and Algorithm.
His research in Artificial intelligence intersects with topics in Absorption and Pattern recognition.
His Pattern recognition study combines topics in areas such as Annotation and Motion.
Ko Nishino conducts interdisciplinary study in the fields of Computer vision and Photography through his research.
He usually deals with Real image and limits it to topics linked to Artificial neural network and Inverse problem and Bidirectional reflectance distribution function.
Ko Nishino has researched Reflectivity in several fields, including Light-field camera, Light field and Normal mapping.
Between 2018 and 2021, his most popular works were:
- Recognizing Material Properties from Images (11 citations)
- Reflectance and Shape Estimation with a Light Field Camera Under Natural Illumination (4 citations)
- Invertible Neural BRDF for Object Inverse Rendering (3 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Algorithm
The scientist’s investigation covers issues in Representation, Real image, Algorithm, Artificial intelligence and Object.
His Real image research is multidisciplinary, incorporating perspectives in 3D reconstruction, Pose and Polygon mesh.
Ko Nishino interconnects Artificial neural network and Point cloud in the investigation of issues within Algorithm.
The concepts of his Artificial neural network study are interwoven with issues in Bidirectional reflectance distribution function, Prior probability and Inverse problem.
His Multispectral image study in the realm of Artificial intelligence connects with subjects such as Surface finish.
His Object research incorporates elements of Visualization, Face and Set.
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