DeLTA 2021 : 2nd International Conference on Deep Learning Theory and Applications

  in Conferences   Posted on November 2, 2020

Conference Information

Submission Deadline Tuesday 16 Feb 2021 Proceedings indexed by :
Conference Dates Jul 7, 2021 - Jul 9, 2021
Conference Address Lieusaint, France
Conference & Submission Link
Conference Organizers : ( Deadline extended ? Click here to edit )

Conference Call for Papers


2nd International Conference on Deep Learning Theory and Applications DeLTA


July 7 – 9, 2021 Lieusaint – Paris, France

In Cooperation with: INNS and AAAI.

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


Regular Paper Submission: February 16, 2021

Authors Notification (regular papers): April 15, 2021

Final Regular Paper Submission and Registration: April 29, 2021

Position Paper Submission: April 1, 2021

Authors Notification (position papers): May 6, 2021

Final Regular Paper Submission and Registration: May 19, 2021


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)

– Sparse Coding

– Neuro-Fuzzy Algorithms

– Evolutionary Methods

– Convolutional Neural Networks (CNN)

– Deep Hierarchical Networks (DHN)

– Dimensionality Reduction

– Unsupervised Feature Learning

– Deep Boltzmann Machines

– Generative Adversarial Networks (GAN)

– Autoencoders

– Deep Belief Networks

Area 2: Machine Learning

– Active Learning

– Meta-Learning and Deep Networks

– Deep Metric Learning Methods

– MAP Inference in Deep Networks

– 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

– Data Tagging

– Fast Information Retrieval

– Scalability of Models

– Data Integration and Fusion

– High-Dimensional Data

– Streaming Data

– Genomics and Bioinformatics

Area 4: Computer Vision Applications

– Image Classification

– Object Detection

– Face Recognition

– Facial Expression Analysis

– Action Recognition

– Human Pose Estimation

– Image Retrieval

– Semantic Segmentation

– Deep Image Denoising

Area 5: Natural Language Understanding

– Sentiment Analysis

– Mobile Text Messaging Applications

– Question Answering Applications

– Speech Interfaces

– Language Translation

– Document Summarization

– Content Filtering on Social Networks

– Recommender Systems


Matias Carrasco Kind, University Illinois Urbana Champaign, United States

Andreas Dengel, German Research Center for Artificial Intelligence (DFKI GmbH), Germany

Barbara Caputo, Politecnico di Torino, Italy


Kurosh Madani, University of Paris-EST Créteil (UPEC), France


Ana Fred, Instituto de Telecomunicações and University of Lisbon, Portugal


DeLTA Secretariat

Address: Avenida de S. Francisco Xavier, Lote 7 Cv. C

Tel: +351 265 520 185

Fax: +351 265 520 186



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