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Call for Papers

DeLTA is sponsored by INSTICC – Institute for Systems and Technologies of Information, Control and Communication

SCOPE

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.

CONFERENCE AREAS

Each of these topic areas is expanded below but the sub-topics list is not exhaustive. Papers may address one or more of the listed sub-topics, although authors should not feel limited by them. Unlisted but related sub-topics are also acceptable, provided they fit in one of the following main topic areas:

1. MODELS AND ALGORITHMS
2. MACHINE LEARNING
3. BIG DATA ANALYTICS
4. COMPUTER VISION APPLICATIONS
5. NATURAL LANGUAGE UNDERSTANDING


AREA 1: MODELS AND ALGORITHMS


  • Recurrent Neural Network (RNN)
  • Evolutionary Methods
  • Convolutional Neural Networks (CNN)
  • Deep Hierarchical Networks (DHN)
  • Dimensionality Reduction
  • Unsupervised Feature Learning
  • Generative Adversarial Networks (GAN)
  • Autoencoders

AREA 2: MACHINE LEARNING


  • Active Learning
  • Meta-Learning and Deep Networks
  • Deep Metric Learning Methods
  • Deep Reinforcement Learning
  • Learning Deep Generative Models
  • Deep Kernel Learning
  • Graph Representation Learning
  • Gaussian Processes for Machine Learning
  • Clustering, Classification and Regression
  • Classification Explainability

AREA 3: BIG DATA ANALYTICS


  • Extracting Complex Patterns
  • IoT and Smart Devices
  • Security Threat Detection
  • Semantic Indexing
  • Fast Information Retrieval
  • Scalability of Models
  • Data Integration and Fusion
  • High-Dimensional Data
  • Streaming Data

AREA 4: COMPUTER VISION APPLICATIONS


  • Image Classification
  • Object Detection
  • Face Recognition
  • Human Pose Estimation
  • Image Retrieval
  • Semantic Segmentation

AREA 5: NATURAL LANGUAGE UNDERSTANDING


  • Sentiment Analysis
  • Question Answering Applications
  • Language Translation
  • Document Summarization
  • Content Filtering on Social Networks
  • Recommender Systems

KEYNOTE SPEAKERS

Ioannis Pitas, Informatics, Aristotle University of Thessaloniki, Greece
Michal Irani, Weizmann Institute of Science, Israel
João Freitas, PagerDuty, Portugal

PAPER SUBMISSION

Authors can submit their work in the form of a complete paper or an abstract, but please note that accepted abstracts are presented but not published in the proceedings of the conference. Complete papers can be submitted as a Regular Paper, representing completed and validated research, or as a Position Paper, portraying a short report of work in progress or an arguable opinion about an issue discussing ideas, facts, situations, methods, procedures or results of scientific research focused on one of the conference topic areas.

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 acknowledgments section of the paper and any other reference that may disclose the authors’ identity.

When submitting a complete paper please note that 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 that can be found under Guidelines and Templates. After the paper submission has been successfully completed, authors will receive an automatic confirmation e-mail.

PUBLICATIONS

All accepted complete papers will be published in the conference proceedings, under an ISBN reference, on paper and on digital support.
SCITEPRESS is a member of CrossRef (http://www.crossref.org/) and every paper on our digital library is given a DOI (Digital Object Identifier).
The proceedings will be submitted for indexation by SCOPUS, Google Scholar, DBLP, Semantic Scholar, EI and Web of Science / Conference Proceedings Citation Index.

SECRETARIAT

DeLTA Secretariat
Address: Avenida de S. Francisco Xavier, Lote 7 Cv. C
             2900-616 Setúbal - Portugal
Tel.: +351 265 520 185
Fax: +351 265 520 186
e-mail: delta.secretariat@insticc.org
Web: https://delta.scitevents.org

VENUE

Our conference will take place at the Lisbon Marriott Hotel, this 4 star Venue was considered Portugal’s leading conference hotel.

CONFERENCE CO-CHAIRS

Oleg Gusikhin, Global Data Insight & Analytics, Ford Motor Company, United States
Kurosh Madani, LISSI Lab. / Institut Universitaire de Technologie de Sénart, University of Paris-EST Créteil (UPEC), France

PROGRAM CO-CHAIRS

Ana Fred, Instituto de Telecomunicações and Instituto Superior Técnico (University of Lisbon), Portugal
Carlo Sansone, Dipartimento di Ingegneria Elettrica e delle Tecnologie dell'Informazione, University of Naples Federico II, Italy

PROGRAM COMMITTEE MEMBERS

Enrico Blanzieri, University of Trento, Italy
Marco Buzzelli, Dipartimento di Informatica, Sistemistica e Comunicazione, University of Milano - Bicocca, Italy
Claudio Cusano, Dep. of Electrical, Computer and Biomedical Engineering, University of Pavia, Italy
Shyam Diwakar, Amrita Mind Brain Center, Amrita University, India
Ke-Lin Du, Electrical and Computer Engineering, Concordia University Montréal, Canada
Gilles B. Guillot, Data Science, CSL Behring / Swiss Institute for Translational and Entrepreneurial Medicine, Switzerland
Chih-Chin Lai, National University Kaohsiung, Taiwan, Republic of China
Chang-Hsing Lee, Bachelor Program in Industrial Artificial Intelligence, Ming Chi University of Technology, Taiwan, Republic of China
Marco Leo, National Research Council of Italy, Italy
Yung-Hui Li, National Central University, Taiwan, Republic of China
Xingyu Li, Electrical and Computer Engineering, University of Alberta, Canada
Fuhai Li, Institute for informatics, Washington University Saint Louis, United States
Huaqing Li, College of Electronic and Information Engineering, Southwest University, China
Perry D. Moerland, Bioinformatics Laboratory, Amsterdam UMC, University Amsterdam, Netherlands
Tomoyuki Naito, Osaka University, Japan
Le-Minh Nguyen, Japan Advanced Institute of Science and Technology, Japan
Juan J. Pantrigo, Ciencias de la Computación, Arquitectura de Computadores, Lenguajes y Sistemas Informáticos y Estadística e Investigación Operativa, Universidad Rey Juan Carlos, Spain
Oksana Pomorova, Faculty of Mathematics and Computer Science, Department of Mathematical Analysis and Control Theory, University of Lodz, Poland
Mircea-Bogdan Radac, Department of Automation and Applied Informatics, Politehnica University of Timisoara, Romania
Sivaramakrishnan Rajaraman, National Library of Medicine, United States
Jitae Shin, School of Electronic and Electrical Eng., Sungkyunkwan University, Korea, Republic of
Sunghwan Sohn, Health Sciences Research, Mayo Clinic, United States
Minghe Sun, Management Science and Statistics, University Texas San Antonio, United States
Ryszard Tadeusiewicz, Department Of Automatics and Biomedical Engineering, AGH University Science Technology, Poland
Jayaraman Valadi, Center for Informatics, Shiv Nadar University, India
Aalt van Dijk, Wageningen University Research Centre, Netherlands
Theodore Willke, Intel Labs, Intel Corporation, United States
Jianhua Xuan, Dept. of Electrical and Computer Engineering, Virginia Tech, United States
Seokwon Yeom, Daegu University, Korea, Republic of
Yizhou Yu, Department of Computer Science, The University of Hong Kong, Hong Kong

(list not yet complete)

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