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Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, ISSN 1063-6919, 12/2018, pp. 7794 - 7803
Conference Proceeding
2010, 1, ISBN 9781848211766, xiv, 314
This book describes co-design approaches, and establishes the links between the QoC (Quality of Control) and QoS (Quality of Service) of the network and... 
Sensor networks | Design and construction | Reliability | Feedback control systems | SCIENCE | System Theory | Electrical Controls | Computer Science | Automatic Control Engineering
Book
IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP), ISSN 2329-9290, 03/2015, Volume 23, Issue 3, pp. 517 - 529
Journal Article
Hydrology and Earth System Sciences, ISSN 1027-5606, 2013, Volume 17, Issue 1, pp. 253 - 267
Despite theoretical benefits of recurrent artificial neural networks over their feedforward counterparts, it is still unclear whether the former offer... 
FEEDFORWARD | GEOSCIENCES, MULTIDISCIPLINARY | RESERVOIR COMPUTING APPROACH | RECURRENT | SYSTEMS | WATER RESOURCES | ALGORITHMS | FEEDBACK | PREDICTION | Models | Neural networks | Runoff | Rain and rainfall | Streamflow | Analysis | Training | Networks | Hydrology | Artificial neural networks | Modelling | Feedforward | River basins
Journal Article
Journal Article
2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), ISSN 1063-6919, 06/2015, Volume 7-12-, pp. 3547 - 3555
This paper addresses the problem of pixel-level segmentation and classification of scene images with an entirely learning-based approach using Long Short Term... 
Accuracy | Weaving | Feedforward neural networks | Roads | Networks | Recurrent neural networks | State of the art | Segmentation | Classification | Images | Two dimensional | Texture
Conference Proceeding
IEEE Transactions on Power Systems, ISSN 0885-8950, 05/2018, Volume 33, Issue 3, pp. 3265 - 3275
Scenario generation is an important step in the operation and planning of power systems with high renewable penetrations. In this work, we proposed a... 
Training | Wind | Renewable integration | deep learning | scenario generation | generative models | Probabilistic logic | Generators | Gallium nitride | Power generation | Autoregressive processes | WIND | METHODOLOGY | UNCERTAINTY | ENGINEERING, ELECTRICAL & ELECTRONIC | Probabilistic models | Probabilistic methods | Conditioning | Feedforward | Neural networks
Journal Article
Journal Article
Hydrology and Earth System Sciences, ISSN 1027-5606, 10/2003, Volume 7, Issue 5, pp. 693 - 706
Recently Feed-Forward Artificial Neural Networks (FNN) have been gaining popularity for stream flow forecasting. However, despite the promising results... 
Rainfall-runoff | Artificial Neural Networks | Forecasting | Stream-flow | stream-flow | artificial neural networks | GEOSCIENCES, MULTIDISCIPLINARY | rainfall-runoff | forecasting | RIVER FLOW PREDICTION | WATER RESOURCES | FEEDFORWARD NETWORKS | RAINFALL-RUNOFF MODEL
Journal Article
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, ISSN 1942-4787, 03/2017, Volume 7, Issue 2, pp. e1200 - n/a
Journal Article