Data clustering is an essential technique for analyzing complex datasets and continues to be a central research topic in data *** clustering algorithms,such as K-means,are widely used due to their simplicity and *** p...
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Data clustering is an essential technique for analyzing complex datasets and continues to be a central research topic in data *** clustering algorithms,such as K-means,are widely used due to their simplicity and *** paper proposes a novel Spiral Mechanism-Optimized Phasmatodea Population Evolution Algorithm(SPPE)to improve clustering *** SPPE algorithm introduces several enhancements to the standard Phasmatodea Population Evolution(PPE)***,a Variable Neighborhood Search(VNS)factor is incorporated to strengthen the local search capability and foster population ***,a position update model,incorporating a spiral mechanism,is designed to improve the algorithm’s global exploration and convergence ***,a dynamic balancing factor,guided by fitness values,adjusts the search process to balance exploration and exploitation *** performance of SPPE is first validated on CEC2013 benchmark functions,where it demonstrates excellent convergence speed and superior optimization results compared to several state-of-the-art metaheuristic *** further verify its practical applicability,SPPE is combined with the K-means algorithm for data clustering and tested on seven *** results show that SPPE-K-means improves clustering accuracy,reduces dependency on initialization,and outperforms other clustering *** study highlights SPPE’s robustness and efficiency in solving both optimization and clustering challenges,making it a promising tool for complex data analysis tasks.
In this paper, a high-precision three-dimensional (3-D) near-field (NF) localization method is proposed under an underdetermined case based on a symmetric enhanced nested array (SENA). Firstly, the symmetry of the arr...
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In recent years, deep learning-based synthetic aperture radar (SAR) image detection, recognition, and segmentation models achieve remarkable accuracy when trained on large amounts of SAR image samples. However, the ac...
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PDF -to-audio based summarization technology is designed to enhance information accessibility and efficiency by transforming long written reports into short, audible summaries. AI, NLP, and TTS technologies that have ...
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To extract important information from the document images, document layout analysis research has been carried out. Previous research analyzes document layouts only for specific document formats. This paper proposes a ...
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Vehicular Ad Hoc Networks (VANETs) are considered crucial for real-time vehicle-to-vehicle communication, which in turn enhances the efficiency of traffic and road safety. VANETs are very vulnerable to Denial-of-Servi...
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Grape crops are a great source of income for *** yield and quality of grapes can be improved by preventing and treating *** farmer’s yield will be dramatically impacted if diseases are found on grape *** detection ca...
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Grape crops are a great source of income for *** yield and quality of grapes can be improved by preventing and treating *** farmer’s yield will be dramatically impacted if diseases are found on grape *** detection can reduce the chances of leaf diseases affecting other healthy *** studies have been conducted to detect grape leaf diseases,but most fail to engage with end users and integrate the model with real-time mobile *** study developed a mobile-based grape leaf disease detection(GLDD)application to identify infected leaves,Grape Guard,based on a TensorFlow Lite(TFLite)model generated from the You Only Look Once(YOLO)v8 model.A public grape leaf disease dataset containing four classes was used to train the *** results of this study were relied on the YOLO architecture,specifically YOLOv5 and *** extensive experiments with different image sizes,YOLOv8 performed better than ***8 achieved 99.9%precision,100%recall,99.5%mean average precision(mAP),and 88%mAP50-95 for all classes to detect grape leaf *** Grape Guard android mobile application can accurately detect the grape leaf disease by capturing images from grape vines.
Transferable adversarial attacks are a threat to deep neural networks, in particular, for black-box scenarios where access to model information is limited. One can, for example, exploit the intermediate layer neurons ...
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Current visual captioning technologies typically transform 3D/2D visual information into one-dimensional sequential data and employ language models to generate corresponding descriptions. This approach, however, compr...
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Background: Cardiovascular Diseases (CVD) requires precise and efficient diagnostic tools. The manual analysis of Electrocardiograms (ECGs) is labor-intensive, necessitating the development of automated methods to enh...
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