What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Algorithm
Shao-Yi Chien spends much of his time researching Artificial intelligence, Motion estimation, Computer vision, Embedded system and Image segmentation.
Many of his studies on Artificial intelligence apply to Pattern recognition as well.
His research integrates issues of Image processing, Real-time computing, Data compression and Computer hardware in his study of Motion estimation.
His work on Image scaling and Face as part of general Computer vision research is often related to Process and Cropping, thus linking different fields of science.
His work deals with themes such as Color quantization and Cluster analysis, which intersect with Image segmentation.
The study incorporates disciplines such as Image registration and Background subtraction in addition to Segmentation.
His most cited work include:
- Efficient moving object segmentation algorithm using background registration technique (387 citations)
- Analysis and architecture design of an HDTV720p 30 frames/s H.264/AVC encoder (263 citations)
- Analysis and architecture design of variable block-size motion estimation for H.264/AVC (240 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, Computer hardware, Algorithm and Motion estimation.
His study connects Pattern recognition and Artificial intelligence.
His work on Computer graphics expands to the thematically related Computer vision.
His Computer hardware study combines topics from a wide range of disciplines, such as Real-time computing, Hardware architecture, Stream processing and Graphics.
The various areas that he examines in his Algorithm study include Image processing and Interpolation.
Shao-Yi Chien interconnects Macroblock, Frame rate, Motion compensation and Motion vector in the investigation of issues within Motion estimation.
He most often published in these fields:
- Artificial intelligence (50.00%)
- Computer vision (42.98%)
- Computer hardware (17.84%)
What were the highlights of his more recent work (between 2016-2021)?
- Artificial intelligence (50.00%)
- Computer vision (42.98%)
- Convolutional neural network (4.68%)
In recent papers he was focusing on the following fields of study:
Artificial intelligence, Computer vision, Convolutional neural network, Algorithm and Eye tracking are his primary areas of study.
His work is dedicated to discovering how Artificial intelligence, Machine learning are connected with Semantics and other disciplines.
His Computer vision research includes elements of Power consumption and Eye movement.
The concepts of his Convolutional neural network study are interwoven with issues in Computer hardware, Computation, Computer engineering and Speedup.
As part of the same scientific family, Shao-Yi Chien usually focuses on Algorithm, concentrating on Convolution and intersecting with Kernel.
His Eye tracking research includes themes of Image sensor and Gaze.
Between 2016 and 2021, his most popular works were:
- Learning Superpixels with Segmentation-Aware Affinity Loss (46 citations)
- Noise Reduction in ECG Signals Using Fully Convolutional Denoising Autoencoders (40 citations)
- Learning to Compose with Professional Photographs on the Web (34 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Algorithm
Shao-Yi Chien focuses on Artificial intelligence, Computer vision, Convolutional neural network, Feature and Algorithm.
His Artificial intelligence study frequently draws parallels with other fields, such as Pattern recognition.
His Pattern recognition research is multidisciplinary, incorporating elements of Pixel, Noise and Leverage.
His Image, Object and RGB color model study in the realm of Computer vision connects with subjects such as Edge and Tone mapping.
His studies deal with areas such as Ecg signal, Decoding methods, Noise reduction and Computer engineering as well as Convolutional neural network.
Shao-Yi Chien studied Algorithm and Convolution that intersect with Computation, Reverberation and Ensemble learning.
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