What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Optics
- Statistics
Edmund Y. Lam mainly investigates Optics, Artificial intelligence, Image processing, Lithography and Image resolution.
His Optics research is multidisciplinary, incorporating elements of Computational photography, Image restoration and Inverse problem.
Artificial intelligence is closely attributed to Computer vision in his work.
His Image processing study combines topics from a wide range of disciplines, such as Probability distribution, Holography, Total variation denoising, Camera resectioning and Distortion.
His Lithography study combines topics in areas such as Electronic engineering, Robustness, Photolithography and Manufacturing cost.
His Image resolution research incorporates themes from Image sensor, Color constancy, Lens, Superresolution and Iterative reconstruction.
His most cited work include:
- A mathematical analysis of the DCT coefficient distributions for images (616 citations)
- A Total Variation Regularization Based Super-Resolution Reconstruction Algorithm for Digital Video (166 citations)
- Standard cell layout with regular contact placement (158 citations)
What are the main themes of his work throughout his whole career to date?
Edmund Y. Lam mostly deals with Artificial intelligence, Optics, Computer vision, Iterative reconstruction and Image processing.
His work in Artificial intelligence is not limited to one particular discipline; it also encompasses Pattern recognition.
His Optics research includes elements of Image quality and Inverse problem.
As part of the same scientific family, Edmund Y. Lam usually focuses on Inverse problem, concentrating on Lithography and intersecting with Electronic engineering.
Edmund Y. Lam combines subjects such as Algorithm and Fourier transform with his study of Iterative reconstruction.
His research is interdisciplinary, bridging the disciplines of Point spread function and Image processing.
He most often published in these fields:
- Artificial intelligence (36.86%)
- Optics (36.04%)
- Computer vision (27.37%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (36.86%)
- Computer vision (27.37%)
- Optics (36.04%)
In recent papers he was focusing on the following fields of study:
His main research concerns Artificial intelligence, Computer vision, Optics, Deep learning and Iterative reconstruction.
Edmund Y. Lam combines subjects such as Digital holography, Holography and Pattern recognition with his study of Artificial intelligence.
His work is dedicated to discovering how Computer vision, Artificial neural network are connected with Image and Image segmentation and other disciplines.
The Optics study combines topics in areas such as Image processing, Computational photography and Fourier transform.
His Image processing study combines topics in areas such as Speckle noise, Speckle pattern, Synthetic aperture radar, Point spread function and Algorithm.
The concepts of his Computational photography study are interwoven with issues in Optical sensing and Electronic engineering.
Between 2017 and 2021, his most popular works were:
- Learning-based nonparametric autofocusing for digital holography (79 citations)
- End-to-end deep learning framework for digital holographic reconstruction (35 citations)
- 102-nm, 44.5-MHz inertial-free swept source by mode-locked fiber laser and time stretch technique for optical coherence tomography (23 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Optics
- Statistics
His scientific interests lie mostly in Artificial intelligence, Optics, Holography, Computer vision and Convolutional neural network.
His research related to Iterative reconstruction, Deep learning, Image resolution, Image processing and Light field might be considered part of Artificial intelligence.
As a part of the same scientific family, Edmund Y. Lam mostly works in the field of Image processing, focusing on Artificial neural network and, on occasion, Image segmentation.
Edmund Y. Lam interconnects Image quality and Fourier transform in the investigation of issues within Optics.
His work focuses on many connections between Holography and other disciplines, such as Wavefront, that overlap with his field of interest in Electronic engineering, Phase imaging and Holographic imaging.
In his research, Visualization, Fidelity, Noise, Angular spectrum method and Distortion is intimately related to Convolution, which falls under the overarching field of Computer vision.
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