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DTI-RCNN: New Efficient Hybrid Neural Network Model to Predict Drug–Target Interactions by Xiaoping Zheng; Song He; Xinyu Song; Zhongnan Zhang; Xiaochen Bo is a book available to read on EtoBox.

What is DTI-RCNN: New Efficient Hybrid Neural Network Model to Predict Drug–Target Interactions about?

This three-volume set LNCS 11139-11141 constitutes the refereed proceedings of the 27th International Conference on Artificial Neural Networks, ICANN 2018, held in Rhodes, Greece, in October 2018. The papers presented in these volumes was carefully reviewed and selected from  total of 360 submissions. They are related to the following thematic topics: AI and Bioinformatics, Bayesian and Echo State Networks, Brain Inspired Computing, Chaotic Complex Models, Clustering, Mining, Exploratory Analysis, Coding Architectures, Complex Firing Patterns, Convolutional Neural Networks, Deep Learning (DL), DL in Real Time Systems, DL and Big Data Analytics, DL and Big Data, DL and Forensics, DL and Cybersecurity, DL and Social Networks, Evolving Systems – Optimization, Extreme Learning Machines, From Neurons to Neuromorphism, From Sensation to Perception, From Single Neurons to Networks, Fuzzy Modeling, Hierarchical ANN, Inference and Recognition, Information and Optimization, Interacting with The Brain, Machine Learning (ML), ML for Bio Medical systems, ML and Video-Image Processing, ML and Forensics, ML and Cybersecurity, ML and Social Media, ML in Engineering, Movement and Motion Detection,

Author

Xiaoping Zheng; Song He; Xinyu Song; Zhongnan Zhang; Xiaochen Bo

Publisher

Springer International Publishing : Imprint: Springer

Published

2018

Language

EN

ISBN

9783030014193

Subjects

Computer Science, Engineering, Mathematics