Impact Score 5.45
This Special Issue on Effective and Efficient Deep Learning based Solutions seeks for publications presenting new and extended applications of Deep Learning with a special focus on effectiveness and efficiency. Deep Learning has received a lot of attention in the past two decades. Although references to deep models appeared years before, it is in this century that the computational resources have allowed to use these models to solve very complex tasks. This process has not stopped. New advances are continuously presented to address even more complicated and challenging undertakings. However, the size and sophistication of recent models and tasks is constantly growing.In this Special Issue we put the focus on two fundamental characteristics necessary to extend and improve the use of Deep Learning architectures. On the one hand, we look forward for research addressing the efficiency of the models: novel paradigms and approaches to tackle computational resources restrictions limiting the application of these architectures. On the other hand, we also pursue research targeting the effectiveness of these architectures: novel and extended applications of Deep Learning going one step further and enabling to solve problems with robust performance.
TOPICS OF INTEREST
We invite the submission of high quality papers related to one or more of the following topics:
Dr. David Camacho (Lead guest editor)Departamento de Sistemas Informáticos, Universidad Politécnica de Madrid, E-mail: [email protected]
Dr. Alejandro Martín, Departamento de Sistemas Informáticos, Universidad Politécnica de Madrid, E-mail: [email protected]
Submission deadline: 31st December 2020Pre-screening notification: 15th January 2021First round notification: 15th April 2021Revision due: 15th June 2021Final notification: 15th July 2021Final Manuscript due: 15th September 2021
INSTRUCTIONS FOR MANUSCRIPTS
Paper submissions for the special issue should follow the submission format and guidelines (https://www.springer.com/journal/521/submission-guidelines).All the papers will be peer-reviewed following the NCA Journal reviewing procedures. Authors should select “Effective and Efficient Deep Learning Based Solutions” during the submission step 'Additional Information'.The submitted papers must provide original research that has not been published nor currently under review by other venues. Previously published conference papers should be clearly identified by the authors at the submission stage and an explanation should be provided about how such papers have been extended to be considered for this special issue. Extended conference contributions must have at least 80% difference from the original works (the authors must indicate the conference name and make the reference to the base conference paper).
Guest editors will make an initial determination of the suitability and scope of all submissions. Papers will be evaluated based on their originality, presentation, relevance and contributions, as well as their suitability to the special issue. Papers that either lack originality, clarity in presentation or fall outside the scope of the special issue will not be sent for review and the authors will be promptly informed in such cases.A Peer Review procedure will follow in order to perform an objective and robust review of all the manuscripts. Every manuscript will be sent to at least 3 international reviewers, with recognized experience in the field.