An outline of progress in the first year of research activities under my PhD. This is an outline of how and why Deep Learning can be used with remote sensing data for water contents analysis and classification, results from proof of concept experiments are described and future research activities are explained. A recording of the presentation and associated questions is available at https://1drv.ms/v/s!AsHRpsQE0ig4jPcrly23In5Tbqd10
Central to the looming paradigm shift toward data-intensive science, machine-learning techniques are...
In the big data era of earth observation, deep learning and other data mining technologies become cr...
Treball de Final de Màster Universitari Erasmus Mundus en Tecnologia Geoespacial (Pla de 2013). Codi...
PosterEnvironmental monitoring and early warning of water quality from space is now feasible at unpr...
Deep learning has revolutionized computer vision and natural language processing with various algori...
Recent launches of high-resolution satellite sensors mean Earth Observation data are available at an...
The human brain is easily the most complex structure in the known universe. Its processing power com...
Deep Learning: A subfield of machine learning; Algorithms inspired by function of the brain; Scales ...
Since 2012, Deep Learning with Convolutional Neural Networks (CNNs) is the state of the art approach...
Logistical and financial limitations of underwater operations are inherent in marine science, includ...
Logistical and financial limitations of underwater operations are inherent in marine science, includ...
Recent advances in satellite technology have led to a regular, frequent and high- resolution monitor...
We provided a new dataset for deep learning of surface water features on Sentinel-2 satellite images...
Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science...
Deep learning methods are often used for image classification or local object segmentation. The corr...
Central to the looming paradigm shift toward data-intensive science, machine-learning techniques are...
In the big data era of earth observation, deep learning and other data mining technologies become cr...
Treball de Final de Màster Universitari Erasmus Mundus en Tecnologia Geoespacial (Pla de 2013). Codi...
PosterEnvironmental monitoring and early warning of water quality from space is now feasible at unpr...
Deep learning has revolutionized computer vision and natural language processing with various algori...
Recent launches of high-resolution satellite sensors mean Earth Observation data are available at an...
The human brain is easily the most complex structure in the known universe. Its processing power com...
Deep Learning: A subfield of machine learning; Algorithms inspired by function of the brain; Scales ...
Since 2012, Deep Learning with Convolutional Neural Networks (CNNs) is the state of the art approach...
Logistical and financial limitations of underwater operations are inherent in marine science, includ...
Logistical and financial limitations of underwater operations are inherent in marine science, includ...
Recent advances in satellite technology have led to a regular, frequent and high- resolution monitor...
We provided a new dataset for deep learning of surface water features on Sentinel-2 satellite images...
Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science...
Deep learning methods are often used for image classification or local object segmentation. The corr...
Central to the looming paradigm shift toward data-intensive science, machine-learning techniques are...
In the big data era of earth observation, deep learning and other data mining technologies become cr...
Treball de Final de Màster Universitari Erasmus Mundus en Tecnologia Geoespacial (Pla de 2013). Codi...