What is he best known for?
The fields of study he is best known for:
- Computer vision
- Artificial intelligence
- Pixel
Eran Steinberg mostly deals with Computer vision, Artificial intelligence, Digital image, Image processing and Binary image.
His research on Computer vision frequently connects to adjacent areas such as Pattern recognition.
His study brings together the fields of Password and Artificial intelligence.
His research integrates issues of Classifier, Image formation, Filter and Image texture in his study of Digital image.
He studies Image processing, namely Digital image processing.
The various areas that Eran Steinberg examines in his Binary image study include Clipping and Image restoration.
His most cited work include:
- Real-time face tracking in a digital image acquisition device (312 citations)
- Method and apparatus for configuring a camera through external means (292 citations)
- Camera network communication device (274 citations)
What are the main themes of his work throughout his whole career to date?
Eran Steinberg mainly focuses on Computer vision, Artificial intelligence, Digital image, Image processing and Image.
The Computer vision study combines topics in areas such as Flash and Computer graphics.
His Artificial intelligence study frequently links to related topics such as Filter.
His work deals with themes such as Image resolution, Feature detection, Facial recognition system, Image texture and Image formation, which intersect with Digital image.
His work on Image restoration and Clipping as part of general Image processing study is frequently connected to Process and Digital photography, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
The Image acquisition research he does as part of his general Image study is frequently linked to other disciplines of science, such as Foreground-background, therefore creating a link between diverse domains of science.
He most often published in these fields:
- Computer vision (82.27%)
- Artificial intelligence (82.27%)
- Digital image (58.87%)
What were the highlights of his more recent work (between 2008-2014)?
- Artificial intelligence (82.27%)
- Computer vision (82.27%)
- Digital image (58.87%)
In recent papers he was focusing on the following fields of study:
Artificial intelligence, Computer vision, Digital image, Image and Image processing are his primary areas of study.
His biological study spans a wide range of topics, including Flash and Computer graphics.
His study in the field of Image formation, Digital imaging and Digital camera also crosses realms of Low resolution and Mathematics.
The concepts of his Digital image study are interwoven with issues in Pixel, Facial recognition system and Filter.
He interconnects Mechanism, Aperture and Pattern recognition in the investigation of issues within Image.
His Binary image and Digital image processing study in the realm of Image processing interacts with subjects such as Handset and Upload.
Between 2008 and 2014, his most popular works were:
- Classification and Organization of Consumer Digital Images Using Workflow, and Face Detection and Recognition (250 citations)
- Classification system for consumer digital images using automatic workflow and face detection and recognition (182 citations)
- Detecting orientation of digital images using face detection information (168 citations)
In his most recent research, the most cited papers focused on:
- Computer vision
- Artificial intelligence
- Pixel
Eran Steinberg focuses on Artificial intelligence, Computer vision, Digital image, Face detection and Pixel.
His Artificial intelligence research incorporates elements of Workflow and Pattern recognition.
The study incorporates disciplines such as Digital imaging, Tracking and Facial motion capture in addition to Pattern recognition.
Eran Steinberg merges Computer vision with Mathematics in his study.
He combines subjects such as Brightness and Video image with his study of Image processing.
His studies in Orientation integrate themes in fields like Image resolution, Image analysis and Color balance.
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