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DeLTA 2022 : 3rd International Conference on Deep Learning Theory and Applications

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Link: https://delta.scitevents.org
 
When Jul 12, 2022 - Jul 14, 2022
Where Lisbon, Portugal
Submission Deadline Mar 2, 2022
Notification Due Apr 28, 2022
Final Version Due May 12, 2022
Categories    machine learning   neural networks   IOT   big data
 

Call For Papers

CALL FOR PAPERS
3rd International Conference on Deep Learning Theory and Applications DeLTA

website: https://delta.scitevents.org

July 12 - 14, 2022 Lisbon, Portugal


Proceedings will be submitted for indexation by: SCOPUS, Google Scholar, DBLP, Semantic Scholar, Microsoft Academic, EI and Web of Science / Conference Proceedings Citation Index.


IMPORTANT DATES:

Regular Paper Submission: March 2, 2022
Authors Notification (regular papers): April 28, 2022
Final Regular Paper Submission and Registration: May 12, 2022


Position Paper Submission: April 14, 2022
Authors Notification (position papers): May 19, 2022
Final Regular Paper Submission and Registration: June 1, 2022

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 Topics:
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




DeLTA CONFERENCE CO-CHAIRS:
Oleg Gusikhin, Ford Motor Company, United States
Kurosh Madani, University of Paris-EST Créteil (UPEC), France

DeLTA PROGRAM CO-CHAIRS:
Ana Fred, Instituto de Telecomunicações and University of Lisbon, Portugal
Carlo Sansone, University of Naples Federico II, Italy

PROGRAM COMMITTEE
https://delta.scitevents.org/ProgramCommittee.aspx

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

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