Workshop on Deep Learning Applications (DeLA)

Scope

Deep learning is an artificial intelligence (AI) function that imitates the workings of the human brain in processing data and creating patterns for use in decision making. Deep learning is a subset of machine learning in artificial intelligence that has networks capable of learning unsupervised from data that is unstructured or unlabeled. Also known as deep neural learning or deep neural network.

The objective of the workshop on Deep Learning Applications is an opportunity for researchers to provide further insight into the problems solved at this stage, advantages and disadvantages of the various approaches used, lessons learned, and meaningful contributions to enhance applications based on deep learning. In this sense, the first workshop on Deep Learning Applications (DeLA) will provide a forum for the presentation and discussion of novel research ideas or actual deployments focused on the development of advanced applications based on Deep Learning.


Topics

The topics of interest for this special session include, but are not limited to:

  • Chatbots
  • Natural Language Processing (NLP)
  • Computer Vision
  • Sentiment Analysis
  • Speech Recognition
  • Autonomous Vehicles
  • Robotics
  • Image Detection and Object Classification
  • Deep Learning Business Applications
  • Healthcare
  • Entertainment
  • Composing Music
  • Pattern Recognition
  • Action Recognition
  • Virtual Assistants
  • Facial Recognition Systems
  • Fraud Detection
  • Forecasting Solutions
  • eXplainable Artificial Intelligence (XAI)
     

Organizing Committee

  • Dalila Durães (University of Minho, Portugal)
  • Flávio A. O. Santos (Universidade Federal de Pernambuco, Recife, Brazil)
  • Cleber Zanchettin (Universidade Federal de Pernambuco, Recife, Brazil)
  • Leonardo Nogueira Matos (Universidade Federal de Sergipe, São Cristóvão, Brazil)

Program Committee

  • Maynara Donato de Souza (Universidade Federal de Pernambuco, Recife, Brazil)
  • Michael Oliveira da Cruz (Universidade Federal Rural de Pernambuco, Serra, Brazil)
  • Luís Conceição (GECAD-ISEP, Polytechnic of Porto, Portugal)
  • Diogo Martinho (GECAD-ISEP, Polytechnic of Porto, Portugal)
  • Francisco Marcondes (University of Minho, Braga, Portugal)
  • Manuel Rodrigues (University of Minho, Braga, Portugal)

Contact

Dalila Durães
dad@di.uminho.pt

General deadlines

  • Deadline

    7th March, 2025

  • Workshop deadline

    14th March, 2025

  • Demonstrations deadline

    21st March, 2025

  • Notification of acceptance

    25th April, 2025

  • Camera-Ready papers

    9th May, 2025

  • Conference Celebration

    25th-27th June, 2025

Submission

All proposed papers must be submitted in electronic form (PDF format) using the PAAMS conference management system.