What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Visual perception
- Neuroscience
His scientific interests lie mostly in Perception, Perceptual learning, Visual perception, Communication and Stimulus.
In his papers, Shaul Hochstein integrates diverse fields, such as Perception and Association.
The various areas that he examines in his Perceptual learning study include Cognitive psychology, Feature, Hierarchy theory, Speech recognition and Visual cortex.
His work in Hierarchy theory addresses subjects such as Cognitive science, which are connected to disciplines such as Visual learning and Categorical variable.
His Communication study integrates concerns from other disciplines, such as Retina, Visual search, Artificial intelligence and Pattern recognition.
His Stimulus research incorporates themes from Electrophysiology, Biophysics and Blue light.
His most cited work include:
- View from the top: hierarchies and reverse hierarchies in the visual system. (1095 citations)
- The Reverse Hierarchy Theory of Visual Perceptual Learning (734 citations)
- Task difficulty and the specificity of perceptual learning. (670 citations)
What are the main themes of his work throughout his whole career to date?
Shaul Hochstein focuses on Perception, Artificial intelligence, Cognitive psychology, Stimulus and Communication.
His Perception research is multidisciplinary, incorporating perspectives in Visual search and Binocular vision.
Shaul Hochstein has researched Cognitive psychology in several fields, including Visual field and Social psychology.
His Stimulus research incorporates elements of Biophysics, Visual cortex and Optics.
Shaul Hochstein has researched Communication in several fields, including Face and Information processing.
Shaul Hochstein combines subjects such as Cognitive science and Hierarchy theory with his study of Visual perception.
He most often published in these fields:
- Perception (33.58%)
- Artificial intelligence (33.58%)
- Cognitive psychology (29.20%)
What were the highlights of his more recent work (between 2009-2021)?
- Cognitive psychology (29.20%)
- Perception (33.58%)
- Artificial intelligence (33.58%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Cognitive psychology, Perception, Artificial intelligence, Visual perception and Perceptual learning.
His Cognitive psychology study incorporates themes from Attentional blink, Social psychology and Unconscious mind.
His Perception study combines topics from a wide range of disciplines, such as Stimulus, Visual field, Communication and Set.
His Artificial intelligence research is multidisciplinary, incorporating elements of Natural language processing, Machine learning, Computer vision and Pattern recognition.
His Visual perception research focuses on Salient and how it connects with Psychophysics, Orienting response and Perceptual Disorders.
His Perceptual learning study deals with Transfer of training intersecting with Implicit learning.
Between 2009 and 2021, his most popular works were:
- The wide window of face detection. (45 citations)
- Momentary fluctuations in allocation of attention: Cross-modal effects of visual task load on auditory discrimination (35 citations)
- Perceiving set mean and range: Automaticity and precision. (21 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Neuroscience
- Perception
Shaul Hochstein mostly deals with Cognitive psychology, Perception, Visual perception, Artificial intelligence and Categorization.
His Cognitive psychology research includes elements of Change detection, Stimulus, Neuroscience, Mismatch negativity and Field.
The concepts of his Perception study are interwoven with issues in Orientation, Visual field and Facial expression, Communication.
His biological study spans a wide range of topics, including Discrimination learning, Transfer of training, Perceptual learning and Feature.
His research investigates the connection with Visual perception and areas like Salient which intersect with concerns in Perceptual Disorders, Hierarchy theory and Psychophysics.
His studies deal with areas such as Representation, Object, Concept learning, Machine learning and Brain mapping as well as Categorization.
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