What is she best known for?
The fields of study she is best known for:
- Artificial intelligence
- Computer vision
- Geometry
Her primary areas of investigation include Artificial intelligence, Computer vision, Visual search, Perception and Visualization.
The study incorporates disciplines such as Set and Pattern recognition in addition to Artificial intelligence.
Ruth Rosenholtz integrates Computer vision and User interface in her studies.
Ruth Rosenholtz combines subjects such as Peripheral vision and Crowding with her study of Visual search.
Her research in Perception intersects with topics in Motion, Cognitive psychology and Linear separability.
Her Visualization research includes themes of Clipping and Spatial cognition.
Her most cited work include:
- Measuring visual clutter. (446 citations)
- Halo: a technique for visualizing off-screen objects (288 citations)
- A summary statistic representation in peripheral vision explains visual search. (256 citations)
What are the main themes of her work throughout her whole career to date?
Her scientific interests lie mostly in Artificial intelligence, Computer vision, Perception, Pattern recognition and Peripheral vision.
Her Artificial intelligence research incorporates themes from Natural language processing and Set.
Ruth Rosenholtz has included themes like Visualization and Visual field in her Computer vision study.
She has researched Perception in several fields, including Illusion, Cognitive psychology and Representation.
In her work, Vision science is strongly intertwined with Visual perception, which is a subfield of Peripheral vision.
As part of the same scientific family, she usually focuses on Visual search, concentrating on Communication and intersecting with Psychophysics.
She most often published in these fields:
- Artificial intelligence (47.06%)
- Computer vision (27.94%)
- Perception (19.12%)
What were the highlights of her more recent work (between 2017-2021)?
- Peripheral vision (16.91%)
- Perception (19.12%)
- Human–computer interaction (9.56%)
In recent papers she was focusing on the following fields of study:
Her main research concerns Peripheral vision, Perception, Human–computer interaction, Artificial intelligence and Visual perception.
Her work deals with themes such as Change blindness and Pooling, which intersect with Peripheral vision.
Her Perception study combines topics from a wide range of disciplines, such as Mental representation, Cognitive psychology and Applied psychology.
Her Human–computer interaction research integrates issues from Vision science and Visual attention.
Her Artificial intelligence research is multidisciplinary, incorporating perspectives in Visual processing, Crowding, Neuroimaging, Computer vision and Pattern recognition.
Computer vision connects with themes related to Information visualization in her study.
Between 2017 and 2021, her most popular works were:
- Beyond Bouma's window: How to explain global aspects of crowding? (19 citations)
- Challenges to pooling models of crowding: Implications for visual mechanisms. (16 citations)
- Rapid holistic perception and evasion of road hazards. (8 citations)
In her most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Geometry
Her primary scientific interests are in Peripheral vision, Crowding, Visual perception, Artificial intelligence and Human–computer interaction.
Her biological study spans a wide range of topics, including Cognitive neuroscience of visual object recognition and Pooling.
Her study in Cognitive neuroscience of visual object recognition is interdisciplinary in nature, drawing from both Psychophysics, Perception, Bouma and Existential quantification.
Her Visual perception study integrates concerns from other disciplines, such as Applied psychology and Set.
The Artificial intelligence study combines topics in areas such as Machine learning and Computer vision.
Her Human–computer interaction study incorporates themes from Cognitive load, Advanced driver assistance systems, Human multitasking and Distraction.
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