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Peter Bajcsy
Affiliation
National Institute of Standards and Technology, Gaithersburg, MD
Topic
Cell Imaging,A-priori Knowledge,Abstract Representations,Actin Bundles,Additive Gaussian Noise,Amazon Web Services,Artificial Intelligence Machine Learning,Augmented Model,Blurred Images,Bounding Box,Cell Binding,Cell Image Segmentation,Centroid,Circular Region Of Interest,Co-occurrence Matrix,Computational Platform,Computer Hardware,Containerized,Convolutional Neural Network,Convolutional Neural Network Model,Data Augmentation,Direct Estimates,Drug Discovery,Drug Screening,Gaussian Noise,Generative Adversarial Networks,Generative Adversarial Networks Model,Geometric Transformation,Gray Level Co-occurrence Matrix,Grayscale,Hardware Platform,Height Of The Bounding Box,Image Annotation,Image Segmentation,Image-based Measurements,Improvement In Accuracy,Induced Pluripotent Stem,Integer Values,Intensity Values,Interoperability,Interpolation Model,Labeling Method,Light Labels,Linear Solver,Mean Intensity,Microscopy Images,Microscopy Images Of Cells,Number Of Annotations,Otsu Thresholding,Pairwise Comparisons,
Biography
Peter Bajcsy is a computer scientist at National Institute of Standards and Technology (NIST). His research interests include the automatic transfer of image content to knowledge, image processing, machine learning, and computer and machine vision. Bajcsy received a PhD in electrical and computer engineering from the University of Illinois at Urbana-Champaign. He is a Senior Member of IEEE. Contact him at [email protected].