What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Electrical engineering
His primary scientific interests are in Artificial intelligence, Computer vision, Image, Pixel and Real-time computing.
His work deals with themes such as Brightness, Backlight, Decoding methods and Computer graphics, which intersect with Artificial intelligence.
His study in Decoding methods is interdisciplinary in nature, drawing from both Computational complexity theory and Transform coding, Discrete cosine transform.
His research in Computer graphics tackles topics such as Image code which are related to areas like Image display, Tone scale and Light source.
His Computer vision study is mostly concerned with High dynamic range and Contrast.
The Real-time computing study combines topics in areas such as Standard dynamic range and Computer hardware.
His most cited work include:
- Low-complexity transform and quantization in H.264/AVC (627 citations)
- Display adaptive tone mapping (319 citations)
- System for presenting audio-video content (152 citations)
What are the main themes of his work throughout his whole career to date?
Louis Joseph Kerofsky focuses on Computer vision, Artificial intelligence, Computer graphics, Decoding methods and Backlight.
His Computer vision study often links to related topics such as Brightness.
While working in this field, Louis Joseph Kerofsky studies both Artificial intelligence and Geography.
His Computer graphics study integrates concerns from other disciplines, such as Image code and Light source.
His work carried out in the field of Decoding methods brings together such families of science as Discrete mathematics and Encoding.
His work carried out in the field of Backlight brings together such families of science as Signal and Reduction.
He most often published in these fields:
- Computer vision (42.14%)
- Artificial intelligence (42.14%)
- Computer graphics (22.86%)
What were the highlights of his more recent work (between 2011-2021)?
- Bitstream (8.57%)
- Computer vision (42.14%)
- Artificial intelligence (42.14%)
In recent papers he was focusing on the following fields of study:
Louis Joseph Kerofsky mainly focuses on Bitstream, Computer vision, Artificial intelligence, Computer hardware and Decoding methods.
His research on Artificial intelligence frequently links to adjacent areas such as Computer graphics.
His study in Computer hardware is interdisciplinary in nature, drawing from both Real-time computing and Buffer.
His Real-time computing research incorporates elements of Frame, Process engineering and Accumulator.
The Decoding methods study combines topics in areas such as Entropy, Image and Encoding.
His work on Image quality as part of his general Image study is frequently connected to Metric, thereby bridging the divide between different branches of science.
Between 2011 and 2021, his most popular works were:
- System and Method for Energy Storage Management (43 citations)
- A Hierarchical Control Algorithm for Managing Electrical Energy Storage Systems in Homes Equipped with PV Power Generation (22 citations)
- Display stream compression (21 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Algorithm
- Electrical engineering
His primary areas of investigation include Computer hardware, Real-time computing, Bitstream, Electronic communication and Peaking power plant.
His Computer hardware study combines topics from a wide range of disciplines, such as Frame, State and Electronics.
His Bitstream research incorporates themes from Data link, Pixel, Display stream compression, Buffer and Context-adaptive binary arithmetic coding.
Electronic communication combines with fields such as User equipment, Headroom, Transmitter power output, Executable and Power consumption in his work.
His studies deal with areas such as Process engineering and Energy storage as well as Peaking power plant.
His Energy storage study combines topics in areas such as Energy consumption, Accumulator, Distributed generation and Reliability engineering.
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