Conference Details

1st International Conference On Deep Learning Theory And Applications

  • Engineering
  • Computer and Information Technology
  • Conference
  • Jul 8, 2020 - Jul 10, 2020
  • Not Available
  • Lieusaint - Paris, France
  • Rating:
Paper Submission Date
03-31-20
Registration Date
05-20-20
Acceptance Notification Date
05-07-20

Description

Deep Learning and Big Data Analytics are two major topics of data science, nowadays. Big Data has become important in practice, as many organizations have been collecting massive amounts of data that can contain useful information for business analysis and decisions, impacting existing and future technology. A key benefit of Deep Learning is the ability to process these data and extract high-level complex abstractions as data representations, making it a valuable tool for Big Data Analytics where raw data is largely unlabeled. Machine-learning and artificial intelligence are pervasive in most real-world applications scenarios such as computer vision, information retrieval and summarization from structured and unstructured multimodal data sources, natural language understanding and translation, and many other application domains. Deep learning approaches, leveraging on big data, are outperforming state-of-the-art more “classical” supervised and unsupervised approaches, directly learning relevant features and data representations without requiring explicit domain knowledge or human feature engineering. These approaches are currently highly important in IoT applications.


List of Main Topics

  • machine learning
  • Neural Networks and Artificial Intelligence Machine Learning
  • e-Learning Computers in Education
  • neural networks
  • Neural Rehabilitation and Neuroprosthetics
  • Neuromodulation and Neural Engineering
  • Genomics and Bioinformatics
  • theories models and user evaluation
  • IOT
  • big data
  • Information and Knowledge Management Big Data Computing

Speakers

Not Available


Submission Instructions

Guidelines

Submission Guidelines

Authors should submit a paper in English, carefully checked for correct grammar and spelling, addressing one or several of the conference areas or topics.
Each paper should clearly indicate the nature of its technical/scientific contribution, and the problems, domains or environments to which it is applicable. To facilitate the double-blind paper evaluation method, authors are kindly requested to produce and provide the paper WITHOUT any reference to any of the authors, including the authors’ personal details, the acknowledgements section of the paper and any other reference that may disclose the authors’ identity.

Only original papers should be submitted. Authors are advised to read INSTICC's ethical norms regarding plagiarism and self-plagiarism thoroughly before submitting and must make sure that their submissions do not substantially overlap work which has been published elsewhere or simultaneously submitted to a journal or another conference with proceedings. Papers that contain any form of plagiarism will be rejected without reviews.

All papers must be submitted through the online submission platform PRIMORIS and should follow the instructions and templates provided in the documents here, which are also the templates for the camera-ready submission. After the paper submission has been successfully completed, authors will receive an automatic confirmation e-mail.

All papers presented at the conference venue will be available at the SCITEPRESS Digital Library.


Submission Dates

Paper Date
03-31-20

Registration Fee and Instructions

Basic Registration

These prices apply to both paper authors, i.e. speakers, and non-speakers.

535€ - Member of INSTICC, with lunches included
595€ - Non member, with lunches included

Non-member registrations include a free INSTICC membership valid until the end of 2020, which can be used in this and in subsequent INSTICC conferences throughout 2020.