Výsledky vyhledávání - "Darr, Matthew J."

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Pattern Based Multivariable Regression using Deep Learning (PBMR-DP)

Autor: Francis, Jiztom Kavalakkatt, Kumar, Chandan, Herrera-Gerena, Jansel, Kumar, Kundan, Darr, Matthew J

We propose a deep learning methodology for multivariate regression that is based on pattern recognition that triggers fast learning over sensor data. We used a conversion of sensors-to-image which enables us to take advantage of Computer Vision archi

Externí odkaz: http://arxiv.org/abs/2202.13541

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Volumetric based mass flow estimation on sugarcane harvesters

Autor: Hamdan, Muhammad K. A., Rover, Diane T., Darr, Matthew J., Just, John

Yield monitors on harvesters are a key component of precision agriculture. Mass flow estimation is the critical factor to measure, and having this allows for field productivity analysis, adjustments to machine efficiency, and cost minimization by ens

Externí odkaz: http://arxiv.org/abs/2005.00907

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Generalizable semi-supervised learning method to estimate mass from sparsely annotated images

Autor: Hamdan, Muhammad K. A., Rover, Diane T., Darr, Matthew J., Just, John

Mass flow estimation is of great importance to several industries, and it can be quite challenging to obtain accurate estimates due to limitation in expense or general infeasibility. In the context of agricultural applications, yield monitoring is a

Externí odkaz: http://arxiv.org/abs/2003.03192

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Mass Estimation from Images using Deep Neural Network and Sparse Ground Truth

Autor: Hamdan, Muhammad K A, Rover, Daine T., Darr, Matthew J., Just, John

Supervised learning is the workhorse for regression and classification tasks, but the standard approach presumes ground truth for every measurement. In real world applications, limitations due to expense or general in-feasibility due to the specific

Externí odkaz: http://arxiv.org/abs/1908.04387

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