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Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification
Published 2025“…<p dir="ltr">In recent years, deep learning methods have dramatically improved medical image analysis, though earlier models faced difficulties in capturing intricate spatial and contextual details. …”
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103
Intelligent Bilateral Client Selection in Federated Learning Using Game Theory
Published 2022“…Adopting a random selection strategy would entail substantial problems due to the heterogeneity in terms of data quality, and computational and communication resources across the participants. …”
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masterThesis -
104
Sentiment visualization of correlation of loneliness mapped through social intelligence analysis
Published 2024“…In the second part, interactive visualizations are developed to present the findings in an engaging and intuitive manner. Techniques such as tree maps and radar plots are utilized to transform the analyzed data into visually appealing representations.…”
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Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects
Published 2021“…Recently, due to the enhancement of computing capabilities, the increase of the big data use, and the development of effective algorithms, the deep learning (DL) tool has witnessed a great success in data science. …”
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A Comprehensive Review of Digital Twin Technology in Building Energy Consumption Forecasting
Published 2024“…The digitalization of building energy forecasting systems, enhanced by Energy Digital Twin technology alongside IoT devices and advanced data-driven algorithms, offers substantial improvements in energy management and optimization, servicing, maintenance, and energy-efficient design. …”
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109
A Survey of Machine Learning Innovations in Ambulance Services: Allocation, Routing, and Demand Estimation
Published 2024“…<p dir="ltr">In the realm of Emergency Medical Services (EMS), the integration of Machine Learning (ML) techniques has emerged as a catalyst for revolutionizing ambulance operations. ML algorithms could play a pivotal role in dynamically allocating resources, devising efficient routes, and predicting demand patterns. …”
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110
Soft Sensor for NOx Emission using Dynamical Neural Network
Published 2020“…Neural network model is trained using real data logs of an industrial boiler. Principal Component Analysis (PCA) is used to reduce number of input variables. …”
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111
An Artificial Intelligence Approach for Predictive Maintenance in Electronic Toll Collection System
Published 2019“…Historical data of Dubai Toll Collection System is utilized to investigate multiple machine learning algorithms. …”
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112
I Will Survive: An Event-driven Conformance Checking Approach Over Process Streams
Published 2023“…Online conformance checking deals with finding discrepancies be tween real-life and modeled behavior on data streams. …”
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113
Improving INS/GPS Integration for Mobile Robotics Applications
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doctoralThesis -
114
Communications in electronic textile systems
Published 2017“…Abstract- Electronic textiles (e-textiles) are emerging as a novel method for constructing electronic systems in wearable and large area applications. …”
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conferenceObject -
115
Edge intelligence for network intrusion prevention in IoT ecosystem
Published 2023“…This paper proposes a deep learning-based algorithm to protect the network against Distributed Denial-of-Service (DDoS) attacks, insecure data flow, and similar network intrusions. …”
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A Fully Optical Laser Based System for Damage Detection and Localization in Rail Tracks Using Ultrasonic Rayleigh Waves: A Numerical and Experimental Study
Published 2022“…Finally, a 3D Finite Element simulation was conducted to validate the findings and each observation resulting from the experiments. …”
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Edge intelligence for network intrusion prevention in IoT ecosystem
Published 2023“…This paper proposes a deep learning-based algorithm to protect the network against Distributed Denial-of-Service (DDoS) attacks, insecure data flow, and similar network intrusions. …”
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A new approach and faster exact methods for the maximum common subgraph problem
Published 2017“…A detailed analysis shows that the proposed algorithm requires O((m+1)n) time, which is a superior worst-case bound to those known for previously-analyzed algorithms in the setting of the MCS problem. …”
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conferenceObject