Ayellet Tal spends much of his time researching Artificial intelligence, Computer vision, Segmentation, Pattern recognition and Surface. He regularly ties together related areas like Simple in his Artificial intelligence studies. Ayellet Tal interconnects Visualization and Visibility in the investigation of issues within Computer vision.
The Segmentation study combines topics in areas such as Pascal, Polygon mesh, Computer graphics and Polygon. His study in Pattern recognition is interdisciplinary in nature, drawing from both Kadir–Brady saliency detector, Cognitive neuroscience of visual object recognition, Seam carving and Automatic summarization. His Surface research integrates issues from Artifact, Computer graphics and Applied mathematics.
His main research concerns Artificial intelligence, Computer vision, Algorithm, Computer graphics and Theoretical computer science. The study incorporates disciplines such as Polygon mesh and Pattern recognition in addition to Artificial intelligence. His research integrates issues of Image processing and Object detection in his study of Pattern recognition.
In general Computer vision study, his work on Object often relates to the realm of Focus, thereby connecting several areas of interest. His Algorithm research is multidisciplinary, relying on both Collision detection, Function and Data structure. His Theoretical computer science research is multidisciplinary, incorporating perspectives in Deep learning and Graph drawing, Graph Layout.
Ayellet Tal mainly focuses on Artificial intelligence, Image, Key, Theoretical computer science and Object. Convolutional neural network and Deep learning are the primary areas of interest in his Artificial intelligence study. In his works, Ayellet Tal performs multidisciplinary study on Theoretical computer science and Constraint.
His research investigates the connection between Object and topics such as Data mining that intersect with problems in Function. Lightness is a subfield of Computer vision that Ayellet Tal tackles. The various areas that Ayellet Tal examines in his Shape analysis study include Geometry and topology, Segmentation, Triangle mesh, Computer graphics and Vertex.
Artificial intelligence, Image, Theoretical computer science, Key and Point cloud are his primary areas of study. Ayellet Tal conducts interdisciplinary study in the fields of Artificial intelligence and Recurrent neural network through his research. His research in Image intersects with topics in Natural, Domain, Ideal, Matching and Point.
His Theoretical computer science research is multidisciplinary, incorporating elements of Entropy, Polygon mesh and Convolutional neural network. Data type, Estimation, Data mining, Architecture and Function are fields of study that overlap with his Key research. His Point cloud research is within the category of Computer vision.
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Context-Aware Saliency Detection
Stas Goferman;Lihi Zelnik-Manor;Ayellet Tal.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2012)
Hierarchical mesh decomposition using fuzzy clustering and cuts
Sagi Katz;Ayellet Tal.
international conference on computer graphics and interactive techniques (2003)
Modeling by example
Thomas Funkhouser;Michael Kazhdan;Philip Shilane;Patrick Min.
international conference on computer graphics and interactive techniques (2004)
What Makes a Patch Distinct
Ran Margolin;Ayellet Tal;Lihi Zelnik-Manor.
computer vision and pattern recognition (2013)
How to Evaluate Foreground Maps
Ran Margolin;Lihi Zelnik-Manor;Ayellet Tal.
computer vision and pattern recognition (2014)
Mesh segmentation using feature point and core extraction
Sagi Katz;George Leifman;Ayellet Tal.
The Visual Computer (2005)
The Bloomier filter: an efficient data structure for static support lookup tables
Bernard Chazelle;Joe Kilian;Ronitt Rubinfeld;Ayellet Tal.
symposium on discrete algorithms (2004)
Mesh Segmentation - A Comparative Study
M. Attene;S. Katz;M. Mortara;G. Patane.
ieee international conference on shape modeling and applications (2006)
Content based retrieval of VRML objects: an iterative and interactive approach
Michael Elad;Ayellet Tal;Sigal Ar.
Metamorphosis of Polyhedral Surfaces using Decomposition
Shymon Shlafman;Ayellet Tal;Sagi Katz.
Computer Graphics Forum (2002)
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