Applications of Deep Learning and Reinforcement Learning to Biological Data

Rapid advances in hardware-based technologies during the past decades have opened up new possibilities for life scientists to gather multimodal data in various application domains, such as omics , bioimaging , medical imaging , and (brain/body)-machine interfaces . These have generated novel opportu...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transaction on neural networks and learning systems 2018-06, Vol.29 (6), p.2063-2079
Hauptverfasser:	Mahmud, Mufti, Kaiser, Mohammed Shamim, Hussain, Amir, Vassanelli, Stefano
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial intelligence Bioimaging Biology Biomedical imaging Brain brain–machine interfaces Computational Biology - methods Computational neuroscience Computer architecture Computing costs convolutional neural network (CNN) Data Mining Data models Data processing Data storage Datasets deep autoencoder (DA) deep belief network (DBN) Deep Learning deep learning performance Domains Feature extraction Humans Interfaces Learning algorithms Machine learning Medical imaging Neuroimaging omics recurrent neural network (RNN) Recurrent neural networks Reinforcement Reinforcement (Psychology) Scientists
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!