Task analysis

AI Inspired Intelligent ResourceManagement in Future Wireless Network

AI Inspired Intelligent Resource Management in Future Wireless Network

Abstract In order to improve network performance, including reducing computation delay, transmission delay and bandwidth consumption, edge computing and caching technologies are introduced to the fifth-generation wireless network (5G). However, […]

AI Inspired Intelligent Resource Management in Future Wireless Network Read More »

A Game AI Competition to foster Collaborative AIresearch and development

A Game AI Competition to foster Collaborative AI research and development

Abstract Game AI competitions are important to foster research and development on Game AI and AI in general. These competitions supply different challenging problems that can be translated into other

A Game AI Competition to foster Collaborative AI research and development Read More »

UNIVERSAL MULTI-MODAL DEEP NETWORK FOR CLASSIFICATION AND SEGMENTATION OF MEDICAL IMAGES

Universal multi-modal deep network for classification and segmentation of medical images

Abstract Medical image processing algorithms have traditionally focused on a specific problem or disease per modality. This approach has continued with the wide-spread adoption of deep learning in the last

Universal multi-modal deep network for classification and segmentation of medical images Read More »

Work-in-Progress—The Sudden Requirement to Work from Home Due to COVID-19 Pandemic Restrictions: Attitudes and Changes in Perceived Value of Physical and Immersive Workspaces —

Work-in-Progress—The Sudden Requirement to Work from Home Due to COVID-19 Pandemic Restrictions: Attitudes and Changes in Perceived Value of Physical and Immersive Workspaces

Abstract What begins as an undifferentiated space becomes a place as we get to know it better and endow it with value, space is freedom [1]. The context for this

Work-in-Progress—The Sudden Requirement to Work from Home Due to COVID-19 Pandemic Restrictions: Attitudes and Changes in Perceived Value of Physical and Immersive Workspaces Read More »

TiM-DNN: Ternary In-Memory Acceleratorfor Deep Neural Networks

TiM-DNN: Ternary In-Memory Accelerator for Deep Neural Networks

Abstract The use of lower precision has emerged as a popular technique to optimize the compute and storage requirements of complex deep neural networks (DNNs). In the quest for lower

TiM-DNN: Ternary In-Memory Accelerator for Deep Neural Networks Read More »

Machine Learning and its Emergence in the Modern World and its Contribution to Artificial Intelligence

Machine Learning and its Emergence in the Modern World and its Contribution to Artificial Intelligence

Abstract Machine learning is known as the scientific study of various algorithms and statistics as well as models that can be used to create or perform certain tasks. These tasks

Machine Learning and its Emergence in the Modern World and its Contribution to Artificial Intelligence Read More »

Towards Backward-Compatible Representation Learning

Abstract We propose a way to learn visual features that are compatible with previously computed ones even when they have different dimensions and are learned via different neural network architectures

Towards Backward-Compatible Representation Learning Read More »

Can mHealth Technology Help Mitigate the Effects of the COVID-19 Pandemic?

Can mHealth Technology Help Mitigate the Effects of the COVID-19 Pandemic?

Abstract Goal: The aim of the study herein reported was to review mobile health (mHealth) technologies and explore their use to monitor and mitigate the effects of the COVID-19 pandemic.

Can mHealth Technology Help Mitigate the Effects of the COVID-19 Pandemic? Read More »

The Future of Digital Agriculture: Technologies and Opportunities

The Future of Digital Agriculture: Technologies and Opportunities

Abstract This article presents key technological advances in digital agriculture, which will have a significant impact. Artificial intelligence-based techniques, together with big data analytics, address the challenges of agricultural production

The Future of Digital Agriculture: Technologies and Opportunities Read More »

Diagnosing Rotating Machines With Weakly Supervised Data Using Deep Transfer Learning

Diagnosing Rotating Machines With Weakly Supervised Data Using Deep Transfer Learning

Abstract Rotating machinery fault diagnosis problems have been well-addressed when sufficient supervised data of the tested machine are available using the latest data-driven methods. However, it is still challenging to

Diagnosing Rotating Machines With Weakly Supervised Data Using Deep Transfer Learning Read More »