1994 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions in computer vision and biomedical image processing and outstanding leadership in the IAPR
Artificial intelligence, Computer vision, Image segmentation, Pattern recognition and Segmentation are his primary areas of study. His Artificial intelligence study frequently links to related topics such as Machine learning. His research on Computer vision often connects related topics like Boundary.
His Image segmentation research integrates issues from Object detection, Geometry and Maxima and minima. Martin D. Levine combines subjects such as Motion compensation, Inference and Robustness with his study of Pattern recognition. Martin D. Levine has included themes like Matching, Identification, Cognitive neuroscience of visual object recognition and Knowledge-based systems in his Segmentation study.
His main research concerns Artificial intelligence, Computer vision, Pattern recognition, Segmentation and Image segmentation. His study in Object, Cognitive neuroscience of visual object recognition, Scale-space segmentation, Image processing and Pixel is carried out as part of his Artificial intelligence studies. Martin D. Levine specializes in Scale-space segmentation, namely Segmentation-based object categorization.
His research is interdisciplinary, bridging the disciplines of Robot and Computer vision. His Facial expression research extends to the thematically linked field of Pattern recognition. His Object detection study frequently links to other fields, such as Object-class detection.
Martin D. Levine focuses on Artificial intelligence, Pattern recognition, Computer vision, Classifier and Microbiology. Artificial intelligence and Machine learning are frequently intertwined in his study. His Pattern recognition research is multidisciplinary, incorporating perspectives in Object detection, Deep learning and Iterative reconstruction.
His Computer vision study integrates concerns from other disciplines, such as Event and Salient. He interconnects Cognitive neuroscience of visual object recognition, Appearance based, Normalization, Speech recognition and Convolutional neural network in the investigation of issues within Classifier. The various areas that Martin D. Levine examines in his Microbiology study include Cadaverine, Saliva, Lysine and Biofilm.
His primary areas of investigation include Artificial intelligence, Computer vision, Pattern recognition, Codebook and Video tracking. Many of his studies on Artificial intelligence involve topics that are commonly interrelated, such as Matching. His Computer vision research incorporates themes from Artificial neural network and Robustness.
His research in Pattern recognition intersects with topics in Object detection, Random forest and Facial expression. His study in Codebook is interdisciplinary in nature, drawing from both Pixel and Inference. His Video tracking study incorporates themes from Data mining, Interobject, Motion estimation, Histogram and Background subtraction.
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Vision in Man and Machine
Martin D. Levine.
Tracking deformable objects in the plane using an active contour model
F. Leymarie;M.D. Levine.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1993)
Face Recognition Using the Discrete Cosine Transform
Ziad M. Hafed;Martin D. Levine.
International Journal of Computer Vision (2001)
Registering multiview range data to create 3D computer objects
G. Blais;M.D. Levine.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1995)
Visual Saliency Based on Scale-Space Analysis in the Frequency Domain
Jian Li;M. D. Levine;Xiangjing An;Xin Xu.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2013)
Dynamic Measurement of Computer Generated Image Segmentations
Martin D. Levine;Ahmed M. Nazif.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1985)
Low Level Image Segmentation: An Expert System
Ahmed M. Nazif;Martin D. Levine.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1984)
Simulating the grassfire transform using an active contour model
F. Leymarie;M.D. Levine.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1992)
Range image segmentation based on differential geometry: a hybrid approach
N. Yokoya;M.D. Levine.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1989)
Live cell image segmentation
Kenong Wu;D. Gauthier;M.D. Levine.
IEEE Transactions on Biomedical Engineering (1995)
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