The emergence of interconnected UAVs has given rise to the creation of flying ad hoc networks (FANETs) aimed at efficiently facilitating network-dependent services. However, FANET encountered considerable challenges i...
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In order to reconstruct 3D clothed human with accurate fine-grained details from sparse views, we propose a deep cooperating two-level global to fine-grained reconstruction framework that constructs robust global geom...
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The segmentation of head and neck(H&N)tumors in dual Positron Emission Tomography/Computed Tomogra-phy(PET/CT)imaging is a critical task in medical imaging,providing essential information for diagnosis,treatment p...
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The segmentation of head and neck(H&N)tumors in dual Positron Emission Tomography/Computed Tomogra-phy(PET/CT)imaging is a critical task in medical imaging,providing essential information for diagnosis,treatment planning,and outcome *** by the need for more accurate and robust segmentation methods,this study addresses key research gaps in the application of deep learning techniques to multimodal medical ***,it investigates the limitations of existing 2D and 3D models in capturing complex tumor structures and proposes an innovative 2.5D UNet Transformer model as a *** primary research questions guiding this study are:(1)How can the integration of convolutional neural networks(CNNs)and transformer networks enhance segmentation accuracy in dual PET/CT imaging?(2)What are the comparative advantages of 2D,2.5D,and 3D model configurations in this context?To answer these questions,we aimed to develop and evaluate advanced deep-learning models that leverage the strengths of both CNNs and *** proposed methodology involved a comprehensive preprocessing pipeline,including normalization,contrast enhancement,and resampling,followed by segmentation using 2D,2.5D,and 3D UNet Transformer *** models were trained and tested on three diverse datasets:HeckTor2022,AutoPET2023,and *** was assessed using metrics such as Dice Similarity Coefficient,Jaccard Index,Average Surface Distance(ASD),and Relative Absolute Volume Difference(RAVD).The findings demonstrate that the 2.5D UNet Transformer model consistently outperformed the 2D and 3D models across most metrics,achieving the highest Dice and Jaccard values,indicating superior segmentation *** instance,on the HeckTor2022 dataset,the 2.5D model achieved a Dice score of 81.777 and a Jaccard index of 0.705,surpassing other model *** 3D model showed strong boundary delineation performance but exhibited variability across datasets,while the
In the data retrieval process of the Data recommendation system,the matching prediction and similarity identification take place a major role in the *** that,there are several methods to improve the retrieving process...
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In the data retrieval process of the Data recommendation system,the matching prediction and similarity identification take place a major role in the *** that,there are several methods to improve the retrieving process with improved accuracy and to reduce the searching ***,in the data recommendation system,this type of data searching becomes complex to search for the best matching for given query data and fails in the accuracy of the query recommendation *** improve the performance of data validation,this paper proposed a novel model of data similarity estimation and clustering method to retrieve the relevant data with the best matching in the big data *** this paper advanced model of the Logarithmic Directionality Texture Pattern(LDTP)method with a Metaheuristic Pattern Searching(MPS)system was used to estimate the similarity between the query data in the entire *** overall work was implemented for the application of the data recommendation *** are all indexed and grouped as a cluster to form a paged format of database structure which can reduce the computation time while at the searching ***,with the help of a neural network,the relevancies of feature attributes in the database are predicted,and the matching index was sorted to provide the recommended data for given query *** was achieved by using the Distributional Recurrent Neural Network(DRNN).This is an enhanced model of Neural Network technology to find the relevancy based on the correlation factor of the feature *** training process of the DRNN classifier was carried out by estimating the correlation factor of the attributes of the *** are formed as clusters and paged with proper indexing based on the MPS parameter of similarity *** overall performance of the proposed work can be evaluated by varying the size of the training database by 60%,70%,and 80%.The parameters that are considered for performance analysis are Precision
A novel FPN network architecture, which designed to modify and improve the performance of the original YOLOv8 mode to overcome the challenges associated with diminished detection accuracy and sluggish wildfire smoke d...
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1 Introduction The Internet of Things(IoT)has facilitated the development of numerous fields in our ***,some equipment in IoT environment lacks sufficient storage and data processing capabilities[1].A feasible strateg...
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1 Introduction The Internet of Things(IoT)has facilitated the development of numerous fields in our ***,some equipment in IoT environment lacks sufficient storage and data processing capabilities[1].A feasible strategy is to leverage the powerful computing capabilities of cloud servers to process the data within the IoT devices.
This article presents LoRaDIP, a novel low-light image enhancement (LLIE) model based on deep image priors (DIPs). While DIP-based enhancement models are known for their zero-shot learning, their expensive computation...
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Quality assessment is a key problem to be resolved in image processing. Few research works have been designed to analyze the quality of images using different techniques. However, the accuracy involved during the proc...
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Agriculture stands as a linchpin for national prosperity, especially in regions blessed with abundant water and fertile soil, capable of yielding a diverse range of food products crucial for human sustenance. However,...
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Blockchain is used to assess health records digitally, preserving the security and immutability of the records. The goal of this study is to make it easier for patients to access their medical records and to send them...
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