What is he best known for?
The fields of study he is best known for:
- Computer vision
- Artificial intelligence
- Electrical engineering
Kevin E. Spaulding focuses on Artificial intelligence, Computer vision, Color image, Computer graphics and Color depth.
His study in RGB color model, Color histogram, Color balance, Digital image and Image processing falls under the purview of Artificial intelligence.
His research integrates issues of Pixel and Digital image processing in his study of Digital image.
His research on Computer vision often connects related topics like Dither.
His research in Computer graphics intersects with topics in Image sensor, Black level, Engineering drawing and Digital camera.
His Color depth research incorporates elements of High color and Color space.
His most cited work include:
- Method and apparatus for color-correcting multi-channel signals of a digital camera (168 citations)
- Method for cross-device color calibration and enhancement using explicit constraints (138 citations)
- Transforming input color values to device control signals (100 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Artificial intelligence, Computer vision, Digital image, Color space and Computer graphics.
His study in Color image, RGB color model, Color balance, Color histogram and Color depth is done as part of Computer vision.
His Color depth study integrates concerns from other disciplines, such as 3D lookup table and High color.
He has included themes like Pixel, Binary image and Clipping in his Digital image study.
His primary area of study in Color space is in the field of ICC profile.
His Rendering study in the realm of Computer graphics connects with subjects such as Digital photography.
He most often published in these fields:
- Artificial intelligence (76.27%)
- Computer vision (75.14%)
- Digital image (38.42%)
What were the highlights of his more recent work (between 2004-2017)?
- Computer vision (75.14%)
- Artificial intelligence (76.27%)
- Digital image (38.42%)
In recent papers he was focusing on the following fields of study:
Kevin E. Spaulding mostly deals with Computer vision, Artificial intelligence, Digital image, Computer graphics and Pixel.
When carried out as part of a general Computer vision research project, his work on RGB color model, Color image and Digital imaging is frequently linked to work in Geography and Information display, therefore connecting diverse disciplines of study.
His RGB color model research is multidisciplinary, incorporating elements of High color, Color space, ICC profile and Color depth.
His work on Artificial intelligence is being expanded to include thematically relevant topics such as Signal.
In general Computer graphics study, his work on Interactive displays often relates to the realm of Time sequence, thereby connecting several areas of interest.
As a part of the same scientific family, Kevin E. Spaulding mostly works in the field of Pixel, focusing on Inkwell and, on occasion, Algorithm and Computational geometry.
Between 2004 and 2017, his most popular works were:
- Imaging device for capturing self-portrait images (72 citations)
- Color image processing for digital cameras (51 citations)
- Method for controlling interactive display system (42 citations)
In his most recent research, the most cited papers focused on:
- Computer vision
- Artificial intelligence
- Electrical engineering
Kevin E. Spaulding mainly focuses on Digital image, Computer vision, Artificial intelligence, Computer graphics and Image processing.
His work carried out in the field of Digital image brings together such families of science as Image sensor, Digital image processing and Interactive displays.
The concepts of his Digital image processing study are interwoven with issues in RGB color model, False color, Color image and Binary image.
In the field of Computer vision, his study on Digital camera and Field of view overlaps with subjects such as Function and Portrait.
His biological study spans a wide range of topics, including Pixel, Inkwell and Masking.
His Image processing research incorporates themes from Image quality, Image enhancement, Selection and Range.
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