What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Algorithm
Badrinath Roysam spends much of his time researching Artificial intelligence, Computer vision, Tracing, Segmentation and Pattern recognition.
His Artificial intelligence study frequently intersects with other fields, such as Algorithm.
His research in Computer vision intersects with topics in Biological system, Retinal, Fundus and Robustness.
His study focuses on the intersection of Tracing and fields such as Confocal microscopy with connections in the field of Confocal, Cell type, Divide and conquer algorithms, Graphical user interface and Software.
Badrinath Roysam combines subjects such as Block, Wavelet and Fast marching method with his study of Segmentation.
His work in Image segmentation addresses subjects such as Cluster analysis, which are connected to disciplines such as Segmentation-based object categorization, Image processing and Object model.
His most cited work include:
- Image change detection algorithms: a systematic survey (1511 citations)
- Adult SVZ Stem Cells Lie in a Vascular Niche: A Quantitative Analysis of Niche Cell-Cell Interactions (835 citations)
- Improved Automatic Detection and Segmentation of Cell Nuclei in Histopathology Images (522 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, Segmentation, Pattern recognition and Algorithm.
His Artificial intelligence study frequently links to other fields, such as Tracing.
His study in Tracing is interdisciplinary in nature, drawing from both Confocal, Microscope, Software system, Confocal microscopy and Visualization.
His Computer vision study integrates concerns from other disciplines, such as Retina and Retinal.
His Pattern recognition study combines topics in areas such as Software, Feature and Cluster analysis.
His work in Algorithm covers topics such as Massively parallel which are related to areas like Theoretical computer science.
He most often published in these fields:
- Artificial intelligence (58.42%)
- Computer vision (45.54%)
- Segmentation (18.32%)
What were the highlights of his more recent work (between 2010-2021)?
- Artificial intelligence (58.42%)
- Computer vision (45.54%)
- Pattern recognition (15.84%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Artificial intelligence, Computer vision, Pattern recognition, Segmentation and Software.
His Artificial intelligence research focuses on Machine learning and how it connects with Agile software development.
The Image processing research he does as part of his general Computer vision study is frequently linked to other disciplines of science, such as Set, therefore creating a link between diverse domains of science.
His Pattern recognition research includes themes of Routing, Superresolution, Feature and Cluster analysis.
Badrinath Roysam interconnects Autofluorescence, Deep neural networks, Tracking, Immunostaining and Field of view in the investigation of issues within Segmentation.
His Software research focuses on subjects like Biological imaging, which are linked to Software engineering, Information retrieval, Focus and Digital image data.
Between 2010 and 2021, his most popular works were:
- Biological imaging software tools (380 citations)
- A broadly applicable 3-D neuron tracing method based on open-curve snake. (153 citations)
- A broadly applicable 3-D neuron tracing method based on open-curve snake. (153 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Algorithm
Badrinath Roysam mainly focuses on Artificial intelligence, Computer vision, Pathology, Software and Image processing.
Badrinath Roysam regularly ties together related areas like Pattern recognition in his Artificial intelligence studies.
His Computer vision research integrates issues from Cell, Cell signaling, Tracing, Algorithm and Effector.
His Software research is multidisciplinary, relying on both Digital image data, Biological imaging, Focus and Data science.
The various areas that Badrinath Roysam examines in his Image processing study include Cytotoxic T cell, Cell morphology, Biomedical engineering and Microscopy.
His Segmentation research incorporates elements of Stem cell and Neural stem cell.
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