What is he best known for?
The fields of study he is best known for:
- Computer vision
- Artificial intelligence
- Operating system
Petronel Bigioi focuses on Computer vision, Artificial intelligence, Digital image, Image and Face.
Many of his studies on Computer vision involve topics that are commonly interrelated, such as Computer graphics.
His Digital image research incorporates elements of Image resolution, Filter, Classifier, Pixel and Flash.
Petronel Bigioi has researched Filter in several fields, including Detector and Digital camera.
His research integrates issues of Lens, Feature detection, Feature and Artifact in his study of Pixel.
His work on Image acquisition as part of general Image research is frequently linked to Foreground-background, bridging the gap between disciplines.
His most cited work include:
- Classification system for consumer digital images using automatic workflow and face detection and recognition (182 citations)
- Modification of post-viewing parameters for digital images using image region or feature information (165 citations)
- Low-light video frame enhancement (140 citations)
What are the main themes of his work throughout his whole career to date?
Petronel Bigioi mainly investigates Artificial intelligence, Computer vision, Digital image, Image processing and Computer graphics.
His Artificial intelligence research incorporates themes from Lens, Filter and Pattern recognition.
In his study, Image acquisition is strongly linked to Flash, which falls under the umbrella field of Computer vision.
His Digital image research includes themes of Image resolution and Digital camera.
His work carried out in the field of Image processing brings together such families of science as Image quality, Pipeline and Computer hardware.
The Computer graphics study combines topics in areas such as Mobile device and Stereoscopy.
He most often published in these fields:
- Artificial intelligence (66.42%)
- Computer vision (64.96%)
- Digital image (34.31%)
What were the highlights of his more recent work (between 2013-2020)?
- Artificial intelligence (66.42%)
- Computer vision (64.96%)
- Image processing (18.98%)
In recent papers he was focusing on the following fields of study:
Petronel Bigioi mainly focuses on Artificial intelligence, Computer vision, Image processing, Iris recognition and Computer graphics.
His work in the fields of Artificial intelligence, such as Digital imaging, overlaps with other areas such as Sweet spot.
His work in the fields of Computer vision, such as Image and Pixel, intersects with other areas such as Audio signal processing and Active listening.
His Image processing study incorporates themes from Feature, Multimedia, Wide field, Distortion and Electronic engineering.
In Iris recognition, Petronel Bigioi works on issues like IRIS, which are connected to Image quality, Segmentation, Image segmentation and Multi frame.
Petronel Bigioi has included themes like Digital image processing, Image analysis and Real time video in his Computer graphics study.
Between 2013 and 2020, his most popular works were:
- Iris authentication in handheld devices - considerations for constraint-free acquisition (38 citations)
- A convolutional neural network (29 citations)
- Real-time video frame pre-processing hardware (26 citations)
In his most recent research, the most cited papers focused on:
- Computer vision
- Artificial intelligence
- Operating system
His scientific interests lie mostly in Computer vision, Artificial intelligence, Pixel, Biometrics and Iris recognition.
Petronel Bigioi mostly deals with Image in his studies of Computer vision.
His study looks at the relationship between Image and topics such as Convolutional neural network, which overlap with Image processing.
His studies in Pixel integrate themes in fields like Image sensor, Wavelength, Optoelectronics, Lens and Aperture.
The study incorporates disciplines such as Image quality, Classifier, Pupil and Authentication in addition to Biometrics.
His work deals with themes such as RGB color model and Feature vector, which intersect with Iris recognition.
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