Computational Intelligence and Neuroscience

Lightweight Deep Learning Models for Resource Constrained Devices


Publishing date
01 Dec 2022
Status
Published
Submission deadline
15 Jul 2022

Lead Editor

1National Institute of Technology Hamirpur, Hamirpur, India

2Central South University, Changsha, China

3South Valley University, Qena, Egypt


Lightweight Deep Learning Models for Resource Constrained Devices

Description

With recent advancements in computational intelligence, deep learning has gained increased attention from many artificial intelligence (AI) researchers due to its applicability in various areas, including e-healthcare, autonomous cars, surveillance systems, or remote sensing, among others. Deep learning models have the ability to automatically extract the potential features of the given data and so do not require any kind of hand-crafted features for the model building process. However, deep learning models require high computational power and resources, therefore, these models are not well suited for lightweight devices such as mobiles and the Internet of Things (IoT). Additionally, these models require an efficient tuning of the hyper-parameters.

To overcome these problems, we must optimize the architecture and initial parameters of deep learning models in such a fashion that it can be implemented on light weight devices. However, the optimization of deep learning models is a challenging problem since it may compromise the performance. Therefore, light weight deep learning models should be developed in such a fashion that they take less resources for optimal architecture and at the same time improve performance. To achieve this, researchers have started utilizing metaheuristic techniques to efficiently select the initial parameters of deep learning models. Still, the optimization of deep learning architecture is necessary to further investigate the structural and functional properties of these models for lightweight devices.

This Special Issue will provide a platform for researchers to share cutting-edge solutions in the field and to promote research and development activities in light weight deep learning models for multimodal data by publishing high-quality original research and review articles in this rapidly growing interdisciplinary field.

Potential topics include but are not limited to the following:

  • Lightweight deep learning models
  • Metaheuristics-based deep learning models
  • Hardware for lightweight deep learning models
  • Explainable lightweight deep learning models
  • Lightweight deep reinforcement learning models
  • Lightweight deep generative adversarial models
  • Lightweight explainable machine learning models
  • Lightweight deep recurrent neural networks
  • Lightweight deep transfer learning models
  • Lightweight deep learning models for Internet of Things
  • Lightweight deep learning models for medical devices

Articles

  • Special Issue
  • - Volume 2023
  • - Article ID 9840473
  • - Retraction

Retracted: Teachers’ Teaching Ability Promotion Strategies Based on Lightweight Deep Learning Combined with Target Detection Algorithm

Computational Intelligence and Neuroscience
  • Special Issue
  • - Volume 2023
  • - Article ID 9781291
  • - Retraction

Retracted: Application of Lightweight Deep Learning Model in Vocal Music Education in Higher Institutions

Computational Intelligence and Neuroscience
  • Special Issue
  • - Volume 2023
  • - Article ID 9896205
  • - Retraction

Retracted: Mechanism of Hyperbaric Oxygen Combined with Astaxanthin Mediating Keap1/Nrf2/HO-1 Pathway to Improve Exercise Fatigue in Mice

Computational Intelligence and Neuroscience
  • Special Issue
  • - Volume 2023
  • - Article ID 9860371
  • - Retraction

Retracted: Internet of Things Device Identification Algorithm considering User Privacy

Computational Intelligence and Neuroscience
  • Special Issue
  • - Volume 2023
  • - Article ID 9865131
  • - Retraction

Retracted: Exploring the Employment Quality Evaluation Model of Application-Oriented University Graduates by Deep Learning

Computational Intelligence and Neuroscience
  • Special Issue
  • - Volume 2023
  • - Article ID 9897546
  • - Retraction

Retracted: Analysis of Chinese Machine Translation Training Based on Deep Learning Technology

Computational Intelligence and Neuroscience
  • Special Issue
  • - Volume 2023
  • - Article ID 9785216
  • - Retraction

Retracted: Application of Computer 3D Modeling Technology in Graphic Image Design

Computational Intelligence and Neuroscience
  • Special Issue
  • - Volume 2023
  • - Article ID 9851564
  • - Retraction

Retracted: Evaluation of the Physical Education Teaching and Training Efficiency by the Integration of Ideological and Political Courses with Lightweight Deep Learning

Computational Intelligence and Neuroscience
  • Special Issue
  • - Volume 2023
  • - Article ID 9863904
  • - Retraction

Retracted: Consumption Structure Optimization Strategy for Scenic Spots Using the Deep Learning Model under Digital Economy

Computational Intelligence and Neuroscience
  • Special Issue
  • - Volume 2023
  • - Article ID 9827839
  • - Retraction

Retracted: Visualization Display System of Gannan Hakka Paper-Cut Works Based on Computer Graphics Algorithm

Computational Intelligence and Neuroscience

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