Distributed Training and Inference of Deep Learning Models for Multi-Modal Land Cover Classification

Distributed Training and Inference of Deep Learning Models for Multi-Modal Land Cover Classification

Deep Neural Networks (DNNs) have established themselves as a fundamental tool in numerous computational modeling applications, overcoming the challenge of defining use-case-specific feature extraction processing by incorporating this stage into unified end-to-end trainable models. Despite their capa...

Full description

Bibliographic Details
Main Authors: Maria Aspri, Grigorios Tsagkatakis, Panagiotis Tsakalides
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Remote Sensing
Subjects:
distributed deep learning
model parallelization
convolutional neural networks
multi-modal observation classification
land cover classification
Online Access:https://www.mdpi.com/2072-4292/12/17/2670

Similar Items

Similar Items