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Found 19 papers, 1 papers with code
Early Detection of Red Palm Weevil Infestations using Deep Learning Classification of Acoustic Signals
The third step involves the application of different Deep Learning (DL) techniques to classify resulting images into two classes: infested and not infested.
Sustainable Palm Tree Farming: Leveraging IoT and Multi-Modal Data for Early Detection and Mapping of Red Palm Weevil
The Red Palm Weevil (RPW) is a highly destructive insect causing economic losses and impacting palm tree farming worldwide.
Interpretation of immunofluorescence slides by deep learning techniques: anti-nuclear antibodies case study
Nowadays, diseases are increasing in numbers and severity by the hour.
Modeling Complex Object Changes in Satellite Image Time-Series: Approach based on CSP and Spatiotemporal Graph
This paper proposes a method for automatically monitoring and analyzing the evolution of complex geographic objects.
Optimizing Forest Fire Prevention: Intelligent Scheduling Algorithms for Drone-Based Surveillance System
Therefore, this research presented the problem of monitoring task scheduling for drones in the forest monitoring system.
Unlocking the Potential of Medical Imaging with ChatGPT's Intelligent Diagnostics
The proposed system has the potential to enhance decision-making, reduce costs, and improve the capabilities of healthcare providers.
Humans are Still Better than ChatGPT: Case of the IEEEXtreme Competition
Since the release of ChatGPT, numerous studies have highlighted the remarkable performance of ChatGPT, which often rivals or even surpasses human capabilities in various tasks and domains.
Contactless Human Activity Recognition using Deep Learning with Flexible and Scalable Software Define Radio
Specifically, this study investigates the use of Wi-Fi channel state information (CSI) as a novel method of ambient sensing that can be employed as a contactless means of recognizing human activity in indoor environments.
TAU: A Framework for Video-Based Traffic Analytics Leveraging Artificial Intelligence and Unmanned Aerial Systems
Fifth, TAU has a fully independent algorithm for crossroad arbitration based on the data gathered from the different zones surrounding it.
Leveraging Artificial Intelligence Techniques for Smart Palm Tree Detection: A Decade Systematic Review
This study systematically reviews research articles between 2011 and 2021 on artificial intelligence (AI) technology for smart palm tree detection.
Parking Analytics Framework using Deep Learning
With the number of vehicles continuously increasing, parking monitoring and analysis are becoming a substantial feature of modern cities.
Securing the Classification of COVID-19 in Chest X-ray Images: A Privacy-Preserving Deep Learning Approach
In this paper, we propose privacy-preserving deep learning (PPDL)-based approach to secure the classification of Chest X-ray images.
A Deep Learning-based Approach for Real-time Facemask Detection
Several experiments are conducted and show good performances of the proposed approach (99% for training and testing accuracy).
A Hybrid APM-CPGSO Approach for Constraint Satisfaction Problem Solving: Application to Remote Sensing
The proposed approach takes advantage of the group search algorithm (GSO) and the constraint propagation (CP) methods to solve problems related to the remote sensing field.
GuideMe: A Mobile Application based on Global Positioning System and Object Recognition Towards a Smart Tourist Guide
Finding information about tourist places to visit is a challenging problem that people face while visiting different countries.
Randomly Initialized Convolutional Neural Network for the Recognition of COVID-19 using X-ray Images
The performance of this network is evaluated through two public datasets, which are the COVIDx and the enhanced COVID-19 datasets.
An Enhanced Randomly Initialized Convolutional Neural Network for Columnar Cactus Recognition in Unmanned Aerial Vehicle Imagery
Recently, Convolutional Neural Networks (CNNs) have made a great performance for remote sensing image classification.
A Novel CNN-LSTM-based Approach to Predict Urban Expansion
Time-series remote sensing data offer a rich source of information that can be used in a wide range of applications, from monitoring changes in land cover to surveilling crops, coastal changes, flood risk assessment, and urban sprawl.
Weight Initialization Techniques for Deep Learning Algorithms in Remote Sensing: Recent Trends and Future Perspectives
During the last decade, several research works have focused on providing novel deep learning methods in many application fields.
