Scholars@Duke publication: Application of a semantic segmentation convolutional neural network for accurate automatic detection and mapping of solar photovoltaic arrays in aerial imagery

Application of a semantic segmentation convolutional neural network for accurate automatic detection and mapping of solar photovoltaic arrays in aerial imagery

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Camilo, J; Wang, R; Collins, LM; Bradbury, K; Malof, JM

January 11, 2018

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Duke Scholars

Author Jordan Milton Malof Electrical and Computer Engineering

Publication Date

January 11, 2018

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Camilo, J., Wang, R., Collins, L. M., Bradbury, K., & Malof, J. M. (2018). Application of a semantic segmentation convolutional neural network for accurate automatic detection and mapping of solar photovoltaic arrays in aerial imagery.

Camilo, Joseph, Rui Wang, Leslie M. Collins, Kyle Bradbury, and Jordan M. Malof. “Application of a semantic segmentation convolutional neural network for accurate automatic detection and mapping of solar photovoltaic arrays in aerial imagery,” January 11, 2018.

Camilo J, Wang R, Collins LM, Bradbury K, Malof JM. Application of a semantic segmentation convolutional neural network for accurate automatic detection and mapping of solar photovoltaic arrays in aerial imagery. 2018.

Camilo, Joseph, et al. Application of a semantic segmentation convolutional neural network for accurate automatic detection and mapping of solar photovoltaic arrays in aerial imagery. 11 Jan. 2018.

Publication Date

January 11, 2018