Deploying a quantum annealing processor to detect tree cover in aerial imagery of California

Quantum annealing is an experimental and potentially breakthrough computational technology for handling hard optimization problems, including problems of computer vision. We present a case study in training a production-scale classifier of tree cover in remote sensing imagery, using early-generation...

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Veröffentlicht in:	PloS one Jg. 12; H. 2; S. e0172505
Hauptverfasser:	Boyda, Edward, Basu, Saikat, Ganguly, Sangram, Michaelis, Andrew, Mukhopadhyay, Supratik, Nemani, Ramakrishna R.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Public Library of Science 27.02.2017 Public Library of Science (PLoS)
Schlagworte:	Aerial photography Algorithms Analysis Artificial intelligence Biology and Life Sciences California Classification Classifiers Computer and Information Sciences Computer applications Computer science Computer vision Couplings Earth science Earth Sciences Engineering and Technology Environmental Monitoring - instrumentation Environmental Monitoring - methods Feature extraction Forests Hardware Image detection Image Processing, Computer-Assisted International conferences Linear Models Machine Learning Microprocessors Moon Neural networks Objective function Optimization People and places Phase transitions Physical Sciences Qubits (quantum computing) Remote sensing Remote Sensing Technology Reproducibility of Results Rescaling Research and Analysis Methods Scaling Simulated annealing (Mathematics) Software Technology application Texture Training Trees Valleys California
ISSN:	1932-6203, 1932-6203
Online-Zugang:	Volltext
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