Abstract The lighting process is one of the biggest power consumption process that have place in every building, from the total energy consumption of a building 25% to 40% being […]
Frequency Domain Design of Controllers for Lighting Process Read More »
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 »
Abstract In this paper, we propose an AI-FML agent for robotic game of Go and AIoT real-world co-learning applications. The fuzzy machine learning mechanisms are adopted in the proposed model,
AI-FML Agent for Robotic Game of Go and AIoT Real-World Co-Learning Applications Read More »
Abstract Within the next decade, the need for automation, intelligent data handling and pre-processing is expected to increase in order to cope with the vast amount of information generated by
Hacking the AI – the Next Generation of Hijacked Systems Read More »
Abstract Effective pain management can significantly improve the quality of life and outcomes for various types of patients(e.g. elderly, adult, young) and often requires assisted living for a significant number
Abstract Tesla’s full self-driving (FSD) computer is the world’s first purpose-built computer for the highly demanding workloads of autonomous driving. It is based on a new System on a Chip
Compute Solution for Tesla’s Full Self-Driving Computer Read More »
Abstract Deep learning and convolutional neural network technologies are increasingly used in the problems of analysis, segmentation, and recognition of objects in images. In this article, a convolutional neural network
Wildfire Segmentation on Satellite Images using Deep Learning Read More »
Abstract in this paper, we propose a deep learning approach for the segmentation of body parts in computer tomography (CT) localizer images. Such images pose dif[1]culties in the automatic image
Abstract When deep learning models classify the actual data and outlier data, most of them do not have enough information about the outlier, which might cause misclassification. Therefore, there is
Visualization Techniques for Outlier Data Read More »
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 »
