What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
His scientific interests lie mostly in Artificial intelligence, Computer vision, Human–computer interaction, Multimedia and ALARM.
His Artificial intelligence research incorporates elements of Identifier and Pattern recognition.
His study in Computer vision is interdisciplinary in nature, drawing from both Computer graphics and Pattern recognition.
He combines subjects such as Electronic program guide and World Wide Web with his study of Human–computer interaction.
His Multimedia research includes elements of Entertainment and User profile.
The study incorporates disciplines such as Variety, Real-time computing, Face and Video camera in addition to ALARM.
His most cited work include:
- Automatic system for monitoring independent person requiring occasional assistance (346 citations)
- Ball throwing assistant (338 citations)
- System to aid a driver to determine whether to change lanes (290 citations)
What are the main themes of his work throughout his whole career to date?
Srinivas Gutta mainly focuses on Artificial intelligence, Computer vision, Multimedia, World Wide Web and Information retrieval.
His studies link Pattern recognition with Artificial intelligence.
His work on Computer graphics expands to the thematically related Computer vision.
Srinivas Gutta interconnects User profile and Human–computer interaction in the investigation of issues within Multimedia.
Many of his studies on World Wide Web involve topics that are commonly interrelated, such as Electronic program guide.
His Color space study integrates concerns from other disciplines, such as RGB color model and Color depth, Color image.
He most often published in these fields:
- Artificial intelligence (34.01%)
- Computer vision (29.55%)
- Multimedia (15.38%)
What were the highlights of his more recent work (between 2003-2012)?
- Information retrieval (9.72%)
- Computer vision (29.55%)
- Artificial intelligence (34.01%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Information retrieval, Computer vision, Artificial intelligence, World Wide Web and Multimedia.
His work in Information retrieval addresses subjects such as Preference, which are connected to disciplines such as Categorical variable, Sensory cue and Human–computer interaction.
His research in the fields of Color space and Pixel overlaps with other disciplines such as Light source, Transparency and Brightness.
His Artificial intelligence study frequently draws parallels with other fields, such as Identification.
His World Wide Web research integrates issues from Data field and Television programming.
His Multimedia study combines topics from a wide range of disciplines, such as Classifier, The Internet and Compression.
Between 2003 and 2012, his most popular works were:
- Commercial insertion into video streams based on surrounding program content (80 citations)
- Dominant color extraction using perceptual rules to produce ambient light derived from video content (74 citations)
- Incorporation of lead actor information for tv recommenders (54 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Machine learning
His primary areas of investigation include Computer vision, Artificial intelligence, Color space, Color depth and Information retrieval.
His work is connected to RGB color model, Color balance, Color image, ICC profile and Luminance, as a part of Computer vision.
His work deals with themes such as False color and Color histogram, which intersect with RGB color model.
His Artificial intelligence study frequently intersects with other fields, such as Weighting.
The concepts of his Information retrieval study are interwoven with issues in Multimedia, World Wide Web and Preference.
The various areas that Srinivas Gutta examines in his Multimedia study include Classifier and Compression.
This overview was generated by a machine learning system which analysed the scientist’s
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