Absorption, scattering, and colour distortion make underwater photography difficult. Marine biology, underwater archaeology, and surveillance need better underwater photos. This research compares cutting-edge underwat...
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The proceedings contain 23 papers. The topics discussed include: solar powered auto irrigation monitoring system with plant health indication using imageprocessing;large language model and artificial intelligence bas...
ISBN:
(纸本)9798331508692
The proceedings contain 23 papers. The topics discussed include: solar powered auto irrigation monitoring system with plant health indication using imageprocessing;large language model and artificial intelligence based human conversation agent;to enhance graph-based retrieval-augmented generation (RAG) with robust retrieval techniques;automatic timetable generation using neural networks trained by genetic algorithms;assessment of efficient and cost-effective vehicle detection in foggy weather;enhanced detection and prevention of SQL injection and cross-site scripting attacks in web applications: analyzing algorithms and threat modeling approaches;efficient duplicate question detection;and a comprehensive survey on computing services to detect stress and anxiety using smart devices.
Vehicle positioning algorithms are essential for improving traffic management and safety by accurately locating vehicles in real-time, and, thus, minimizing congestion and accidents. They also support the development ...
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ISBN:
(纸本)9798350364309;9798350364293
Vehicle positioning algorithms are essential for improving traffic management and safety by accurately locating vehicles in real-time, and, thus, minimizing congestion and accidents. They also support the development of advanced driver assistance systems and autonomous vehicles, relying on precise positioning data for safe navigation. One of the solutions involves using imageprocessingalgorithms, which can have two approaches. One approach is decentralized, in which each vehicle performs its own computing steps and determines its position concerning the other nearby vehicles. The second approach, proposed in this paper, is centralized, where each vehicle sends data to a server that uses cloud computing to process all the data in real-time. As such, vehicles can create a more comprehensive view of the driving conditions in the area by using either of these two approaches, which can help them anticipate potential hazards and make more informed decisions.
In the context of healthcare and human-computer interaction., this research study provides a thorough analysis of sophisticated computational algorithms for data classification, picture processing, and disease predict...
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To concurrently address the challenges of automatic modulation recognition (AMR) and modulation parameter estimation (MPE) in radar signals, we introduce a multi-task learning (MTL) network architecture designed for i...
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ISBN:
(纸本)9798350351040;9798350351033
To concurrently address the challenges of automatic modulation recognition (AMR) and modulation parameter estimation (MPE) in radar signals, we introduce a multi-task learning (MTL) network architecture designed for intra-pulse multi-parameter recognition through automatic noise reduction. The proposed approach initiates by generating time -frequency image (rn) directly from noisy time-domain signal using a neural network. To effectively capture relevant features from TFls, we employ a VGG-like network Subsequently, the multitask learning framework is utilized to achieve AMR and MPE simultaneously. Four typical intra-pulse modulated signals were simulated in the experiments, simulation results verify the effectiveness and reliability of the proposed algorithms.
The paper presents a description of the developed algorithm for changing the size of a multi-element aperture of a recursive-separable five-stage filter for processing digital images generated by specialized optical s...
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The indoor imaging visible light positioning (VLP) technology based on the image sensor (IS) utilizes existing indoor lighting infrastructure to provide high-precision indoor positioning services. However, due to the ...
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Over the past decade, advancements in cellular phone technology have drastically transformed mobile phones from mere communication devices into powerful mini-computers. The integration of high-quality cameras with sma...
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Bearing faults pose a significant threat to the reliability and efficiency of rotating machinery systems, particularly in wind turbines. Traditional fault diagnosis algorithms often face limitations, such as processin...
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ISBN:
(纸本)9798350360875;9798350360868
Bearing faults pose a significant threat to the reliability and efficiency of rotating machinery systems, particularly in wind turbines. Traditional fault diagnosis algorithms often face limitations, such as processing single signal inputs from each sensor without considering interferences between components. To overcome these shortcomings and leverage the potential of processing multi-dimensional signal inputs, we propose SiamFD-net, a deep learning-based method. Focusing on wind turbine bearing fault diagnosis, our model employs a Siamese network architecture, which distinguishes between similar and dissimilar input pairs. This approach not only addresses the limitations of traditional algorithms but also contributes to mitigating the class imbalance problem commonly encountered in fault diagnosis. Experimental results using the Doosan Wind Turbine bearing dataset demonstrate the comprehensive view and diagnosis capability of our model. Furthermore, we validate the effectiveness of SiamFDnet using the Case Western Reserve University (CWRU) bearing fault diagnosis benchmark dataset. Our code is openly accessible at: https://***/SiamFDnet.
One of the first signs of structural deterioration is cracks in the concrete surface, which is important for maintenance because prolonged exposure will seriously harm the environment. The highly regarded method for i...
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