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A survey on reconfigurable intelligent surfaces assisted multi-access edge computing networks: State of the art and future challenges
This survey provides a comprehensive analysis of the integration of Reconfigurable
Intelligent Surfaces (RIS) with edge computing, underscoring RIS's critical role in advancing …
Intelligent Surfaces (RIS) with edge computing, underscoring RIS's critical role in advancing …
Exploring convolutional neural network architectures for EEG feature extraction
The main purpose of this paper is to provide information on how to create a convolutional
neural network (CNN) for extracting features from EEG signals. Our task was to understand …
neural network (CNN) for extracting features from EEG signals. Our task was to understand …
[HTML][HTML] CGADNet: A Lightweight, Real-Time, and Robust Crosswalk and Guide Arrow Detection Network for Complex Scenes
In the context of edge environments with constrained resources, realizing real-time and
robust crosswalk and guide arrow detection poses a significant challenge for autonomous …
robust crosswalk and guide arrow detection poses a significant challenge for autonomous …
MKD-SFasterNet: A Lightweight Edge Computing Architecture for Mechanical Fault Diagnosis
In the era of intelligent manufacturing, faced with the explosive growth of equipment and
sensor data, deep learning (DL)-based fault diagnosis methods with significant feature …
sensor data, deep learning (DL)-based fault diagnosis methods with significant feature …
Charting New Frontiers: Insights and Future Directions in ML and DL for Image Processing
The Special Issue “Deep and Machine Learning for Image Processing: Medical and Non-
medical Applications” of the MDPI journal Electronics marks a pivotal point in the exploration …
medical Applications” of the MDPI journal Electronics marks a pivotal point in the exploration …
Flexible Precision Vector Extension for Energy Efficient Coarse-Grained Reconfigurable Array AI-Engine
The rapid development of Artificial Intelligence (AI) algorithms has created a need for a
resource-optimised hardware accelerator. Among various platforms, Coarse-Grained …
resource-optimised hardware accelerator. Among various platforms, Coarse-Grained …
INDUSTRIAL SECURITY AND ITS ADVANCEMENT THROUGH THE USE OF EDGE ARTIFICIAL INTELLIGENCE: EDGE AI
Using artificial intelligence (AI) algorithms directly on devices on the edge, such as sensors,
cameras, or gateways, to analyse and react to data in realtime without having to transfer it to …
cameras, or gateways, to analyse and react to data in realtime without having to transfer it to …
Review of Machine Learning Deployment Frameworks
AAP Mourão - 2024 - search.proquest.com
In the rapidly evolving field of mobility services, deploying machine learning models
efficiently in resource-constrained environments, such as those found in IoT applications …
efficiently in resource-constrained environments, such as those found in IoT applications …
[PDF][PDF] Hearables: Deep Matched Filter for Online R-Peak Detection from In-Ear ECG in Mobile Application
In-ear wearables, called Hearables, have been introduced for the monitoring of several
physiological signals, inter alia ECG. However, in-ear ECG has a smaller amplitude and …
physiological signals, inter alia ECG. However, in-ear ECG has a smaller amplitude and …