What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Computer vision
His primary areas of study are Artificial intelligence, Pattern recognition, Visual perception, Detection theory and Eye movement.
His work deals with themes such as Stimulus, Communication, Computer vision and Electroencephalography, which intersect with Artificial intelligence.
In Pattern recognition, he works on issues like Optics, which are connected to Visual processing and Lossless JPEG.
His study looks at the intersection of Visual perception and topics like Speech recognition with Mathematical model and Perceptual learning.
His Detection theory research includes elements of Image processing, Image noise, Observer, Spatial frequency and Psychophysics.
His Eye movement research integrates issues from Visual search and Gaze.
His most cited work include:
- Spatial covert attention increases contrast sensitivity across the CSF: support for signal enhancement☆ (413 citations)
- Visual search: a retrospective. (279 citations)
- A signal detection model predicts the effects of set size on visual search accuracy for feature, conjunction, triple conjunction, and disjunction displays. (238 citations)
What are the main themes of his work throughout his whole career to date?
Artificial intelligence, Computer vision, Visual search, Pattern recognition and Eye movement are his primary areas of study.
The Artificial intelligence study combines topics in areas such as Detection theory, Perception and Communication.
His Computer vision study incorporates themes from Observer and Matched filter.
His Visual search research incorporates themes from Machine learning, Saccadic masking and Contrast.
His work focuses on many connections between Pattern recognition and other disciplines, such as White noise, that overlap with his field of interest in Gaussian noise.
His studies deal with areas such as Gaze-contingency paradigm, Visual processing and Eye tracking as well as Eye movement.
He most often published in these fields:
- Artificial intelligence (60.53%)
- Computer vision (34.87%)
- Visual search (22.04%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (60.53%)
- Computer vision (34.87%)
- Eye movement (19.08%)
In recent papers he was focusing on the following fields of study:
Miguel P. Eckstein mainly investigates Artificial intelligence, Computer vision, Eye movement, Visual search and Perception.
His Artificial intelligence research incorporates elements of Visual field and Pattern recognition.
His Detection theory research extends to Computer vision, which is thematically connected.
His Eye movement study combines topics from a wide range of disciplines, such as Cognitive psychology, Probabilistic logic, Visualization and Medical imaging.
His study in Visual search is interdisciplinary in nature, drawing from both Contrast, Object detection, Foveal and Machine learning, Convolutional neural network.
His work on Visual perception as part of general Perception research is often related to Observer, thus linking different fields of science.
Between 2015 and 2021, his most popular works were:
- Humans, but Not Deep Neural Networks, Often Miss Giant Targets in Scenes (39 citations)
- Object detection through search with a foveated visual system (35 citations)
- Beyond scene gist: Objects guide search more than scene background. (15 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Statistics
His primary scientific interests are in Artificial intelligence, Computer vision, Visual search, Eye movement and Perception.
His Artificial intelligence studies intersect with other disciplines such as ENCODE, Communications system and Generative model.
His Computer vision research is multidisciplinary, relying on both Detection theory, Visual field and Fixation.
His work deals with themes such as Object, Object detection and Foveal, which intersect with Visual search.
Miguel P. Eckstein has included themes like Probabilistic logic, Cognitive psychology, Sensory cue and Eye tracking in his Eye movement study.
His Perception research focuses on Visual perception in particular.
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