Special Issue Information Special Issue Call for Paper Other Special Issues on this journal Closed Special Issues
Quantum Intelligent Systems and Deep Learning

Quantum Intelligent Systems and Deep Learning

Journal
Impact Score 6.43

OFFICIAL WEBSITE

Special Issue Information

Submission Deadline: 30-09-2021
Journal Impact Score: 6.43
Journal Name: Soft Computing
Publisher: Soft Computing
Journal & Submission Website: https://www.springer.com/journal/500

Special Issue Call for Papers

A Special Issue in Soft ComputingOpen to submissions until September 30, 2021

At present, the computational demands for solving complex problems in the computational intelligence area involve big data sets and massive and sophisticated learning structures that use neurons, fuzzy logic, and single and multiple optimization algorithms, frequently combined with traditional techniques; consequently, computational tractability is becoming inefficient. There are two emerging fields that will converge in the near future for solving such complex problems; they are quantum computing and deep learning. Quantum computing based on quantum mechanics principles such as superposition of states, interference, entanglement, and others, is expected to provide an exponential speed up. On the other hand, deep learning models allow the understanding of big data sets; lately, deep learning methods have been extended to incorporate other machine learning methods that include reinforcement learning and transfer learning. The aim of this special issue is to analyze the latest theoretical and practical proposals on Quantum Intelligent Systems and Deep Learning for solving diverse scientific and industrial problems. Quantum algorithms of interest are quantum optimization algorithms, quantum neural networks, quantum algorithms for classification, quantum-inspired algorithms in practice, and hybrid quantum-algorithms for quantum computers. Deep learning algorithms of interest are recent advances in transfer learning, dynamic structures of deep learning, theoretical developments on the background of deep learning, and applications in medicine and autonomous vehicles. Proposals that combine quantum algorithms and deep learning of interest are all those that deal with Transfer learning in Hybrid Classical-Quantum Neural Networks and quantum embeddings for machine learning. In the current literature databases, we can find that the interest in combining these two fields is growing very fast; this, together with the fact that quantum computer technology is advancing in leaps and bounds, the interest of searching different kinds of problems that they can solve efficiently has driven the scientific community to research in this field; which will warranty the attention of the scientific community to this special issue.

Important DatesDeadline of submission: September 30, 2021First round of review – comments to authors: November 30, 2021Revised paper deadline: February 15, 2022Submission of final versions: March 31, 2022

Lead Guest EditorsProf. Oscar Castillo, Tijuana Institute of Technology, Tijuana, Mexico. Prof. Oscar Montiel, Instituto Politécnico Nacional-CITEDI, Tijuana, Mexico.Prof. Fevrier Valdez, Tijuana Institute of Technology, Tijuana, Mexico.

Other Special Issues on this journal

Publisher
Journal Details
Closing date
G2R Score
Advances in Pattern Recognition and Computer Vision, Applications and Systems

Advances in Pattern Recognition and Computer Vision, Applications and Systems

Soft Computing
Closing date: 30-12-2021 G2R Score: 6.43
Quantum Intelligent Systems and Deep Learning

Quantum Intelligent Systems and Deep Learning

Soft Computing
Closing date: 30-09-2021 G2R Score: 6.43

Closed Special Issues

Publisher
Journal Details
Closing date
G2R Score
Soft Computing for Edge-Driven Applications

Soft Computing for Edge-Driven Applications

Soft Computing
Closing date: 30-08-2021 G2R Score: 6.43
Sustainable Development of Smart Cities with Edge Computing Techniques

Sustainable Development of Smart Cities with Edge Computing Techniques

Soft Computing
Closing date: 25-08-2021 G2R Score: 6.43