This paper introduces a new network model - the Image Guidance Encoder-Decoder Model (IG-ED), designed to enhance the efficiency of image captioning and improve predictive accuracy. IG-ED, a fusion of the convolutiona...
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Disasters such as conflagration,toxic smoke,harmful gas or chemical leakage,and many other catastrophes in the industrial environment caused by hazardous distance from the peril are *** calamities are causing massive ...
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Disasters such as conflagration,toxic smoke,harmful gas or chemical leakage,and many other catastrophes in the industrial environment caused by hazardous distance from the peril are *** calamities are causing massive fiscal and human life ***,Wireless Sensors Network-based adroit monitoring and early warning of these dangerous incidents will hamper fiscal and social *** authors have proposed an early fire detection system uses machine and/or deep learning *** article presents an Intelligent Industrial Monitoring System(IIMS)and introduces an Industrial Smart Social Agent(ISSA)in the Industrial SIoT(ISIoT)*** proffered ISSA empowers smart surveillance objects to communicate autonomously with other *** Industrial IoT(IIoT)entity gets authorization from the ISSA to interact and work together to improve surveillance in any industrial *** ISSA uses machine and deep learning algorithms for fire-related incident detection in the industrial *** authors have modeled a Convolutional Neural Network(CNN)and compared it with the four existing models named,FireNet,Deep FireNet,Deep FireNet V2,and Efficient Net for identifying the *** train our model,we used fire images and smoke sensor *** image dataset contains fire,smoke,and no fire *** evaluation,the proposed and existing models have been tested on the *** to the comparative analysis,our CNN model outperforms other state-of-the-art models significantly.
Most augmented reality (AR) pipelines typically involve the computation of the camera’s pose in each frame, followed by the 2D projection of virtual objects. The camera pose estimation is commonly implemented as SLAM...
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The Internet of Things (IoT) has revolutionized our lives, but it has also introduced significant security and privacy challenges. The vast amount of data collected by these devices, often containing sensitive informa...
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With the great development of Multi-Target Tracking(MTT)technologies,many MTT algorithms have been proposed with their own advantages and *** to the fact that requirements to MTT algorithms vary from the application s...
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With the great development of Multi-Target Tracking(MTT)technologies,many MTT algorithms have been proposed with their own advantages and *** to the fact that requirements to MTT algorithms vary from the application scenarios,performance evaluation is significant to select an appropriate MTT algorithm for the specific application *** this paper,we propose a performance evaluation method on the sets of trajectories with temporal dimension specifics to compare the estimated trajectories with the true *** proposed method evaluates the estimate results of an MTT algorithm in terms of tracking accuracy,continuity and ***,its computation is based on a multi-dimensional assignment problem,which is formulated as a computable form using linear *** enhance the influence of recent estimated states of the trajectories in the evaluation,an attention function is used to reweight the trajectory errors at different time ***,simulation results show that the proposed performance evaluation method is able to evaluate many aspects of the MTT *** evaluations are worthy for selecting suitable MTT algorithms in different application scenarios.
Trajectory contains spatial-data generated from traces of moving objects like people, animals, etc. Community generated from trajectories portrays common behaviour. Trajectory clustering based on community-detection i...
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Facial expressions can provide a better understanding of people's mental status and attitudes towards specific things. However, facial occlusion in real world is an unfavorable phenomenon that greatly affects the ...
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One of the hot research topics in propagation dynamics is identifying a set of critical nodes that can influence maximization in a complex *** importance and dispersion of critical nodes among them are both vital fact...
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One of the hot research topics in propagation dynamics is identifying a set of critical nodes that can influence maximization in a complex *** importance and dispersion of critical nodes among them are both vital factors that can influence *** therefore propose a multiple influential spreaders identification algorithm based on spectral graph *** algorithm first quantifies the role played by the local structure of nodes in the propagation process,then classifies the nodes based on the eigenvectors of the Laplace matrix,and finally selects a set of critical nodes by the constraint that nodes in the same class are not adjacent to each other while different classes of nodes can be adjacent to each *** results on real and synthetic networks show that our algorithm outperforms the state-of-the-art and classical algorithms in the SIR model.
Melanoma is the most lethal malignant tumour,and its prevalence is *** detection and diagnosis of skin cancer can alert patients to manage precautions and dramatically improve the lives of ***,deep learning has grown ...
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Melanoma is the most lethal malignant tumour,and its prevalence is *** detection and diagnosis of skin cancer can alert patients to manage precautions and dramatically improve the lives of ***,deep learning has grown increasingly popular in the extraction and categorization of skin cancer features for effective prediction.A deep learning model learns and co-adapts representations and features from training data to the point where it fails to perform well on test *** a result,overfitting and poor performance *** deal with this issue,we proposed a novel Consecutive Layerwise weight Con-straint MaxNorm model(CLCM-net)for constraining the norm of the weight vector that is scaled each time and bounding to a *** method uses deep convolutional neural networks and also custom layer-wise weight constraints that are set to the whole weight matrix directly to learn features *** this research,a detailed analysis of these weight norms is performed on two distinct datasets,International Skin Imaging Collaboration(ISIC)of 2018 and 2019,which are challenging for convolutional networks to *** to thefindings of this work,CLCM-net did a better job of raising the model’s performance by learning the features efficiently within the size limit of weights with appropriate weight constraint *** results proved that the proposed techniques achieved 94.42%accuracy on ISIC 2018,91.73%accuracy on ISIC 2019 datasets and 93%of accuracy on combined dataset.
This paper improves the ill-condition of bone-conducted (BC) speech signal by reducing the eigenvalue expansion. BC speech commonly contains a large spectral dynamic range that causes ill-condition for the classical l...
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