Vehicular Fog Networks (VFNs) have emerged as a promising solution for enabling high-bandwidth, low-latency communication between vehicles and infrastructure. However, the limited resources of Roadside Units (RSUs) po...
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In the event of disasters, establishing an emergency wireless network plays a significant role in ensuring effective communication for rescue operations. It is crucial to establish a network that can efficiently conne...
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In an industry that is enduring a rapid transformation, rowers are gaining access to new technologies that help them improve agricultural yields and resource management. TensorFlow-built chatbots can provide instantan...
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Traditionally, many people still wish to write on pen and paper. However, it has some drawbacks, like accessing and storing physical documents efficiently, searching through them, and sharing them efficiently. Handwri...
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Learning activities interactions between small groups is a key step in understanding team sports *** research focusing on team sports videos can be strictly regarded from the perspective of the audience rather than th...
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Learning activities interactions between small groups is a key step in understanding team sports *** research focusing on team sports videos can be strictly regarded from the perspective of the audience rather than the *** team sports videos such as volleyball and basketball videos,there are plenty of intra-team and inter-team *** this paper,a new task named Group Scene Graph Generation is introduced to better understand intra-team relations and inter-team relations in sports *** tackle this problem,a novel Hierarchical Relation Network is *** all players in a video are finely divided into two teams,the feature of the two teams’activities and interactions will be enhanced by Graph Convolutional Networks,which are finally recognized to generate Group Scene *** evaluation,built on Volleyball dataset with additional 9660 team activity labels,a Volleyball+dataset is proposed.A baseline is set for better comparison and our experimental results demonstrate the effectiveness of our ***,the idea of our method can be directly utilized in another video-based task,Group Activity *** show the priority of our method and display the link between the two ***,from the athlete’s view,we elaborately present an interpretation that shows how to utilize Group Scene Graph to analyze teams’activities and provide professional gaming suggestions.
The objective of this research is to demonstrate the performance difference exhibited by the seam carving algorithm when executed sequentially on a conventional CPU as opposed to when it is run parallelly. Multithread...
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The Recommendation systems gaining importance every passing day and are frequently used in e-commerce websites, content streaming platforms, social media platforms, and other applications to analyze large amounts of d...
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Predictive analytics if combined with machine learning approaches have the potential to play a significant role in forecasting the spread of respiratory infections. Machine learning approaches aid in the mining of dat...
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Routing protocols have an important part to play in maintaining the interoperability of the components that make up the Internet of Things. To make communication amongst the Internet of Things (IoT) a reality, IETF-RO...
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One strategy to prevent COVID-19 as a result of the pandemic is to use a face mask. Although many countries have made it a requirement for citizens to do so, the majority of people continue to disobey this order. In t...
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ISBN:
(纸本)9789819914784
One strategy to prevent COVID-19 as a result of the pandemic is to use a face mask. Although many countries have made it a requirement for citizens to do so, the majority of people continue to disobey this order. In the current situation, police frequently check for face masks in public locations and fine anyone found not to be wearing one. The existing system identifies the person wearing the mask or not, but our proposed method identifies the person those who are not wearing the mask properly and also identifies the multiple person wearing the mask or not. On the other side, some governments have implemented technology to identify individuals wearing face masks and communicate their information to a patrol team so that they may catch them. The proposed model identifies individuals who are in the public without face masks. The proposed approach is able to identify these persons using facial detection technologies, and the data is then combined with a database of public identity information to gather information about the individual and deliver the fine amount to his home address and mobile numbers. Using the convolution neural network (CNN) model, we have identified people wearing and not wearing masks. When compared to many other algorithms, CNN can more precisely recognize data down to the pixel level. In the implementation of our model, the activation functions for the hidden and fully connected layers, respectively, were rectified linear unit (ReLU) and softmax. Two convolution layers with 100 filters each were used. The 91.21% accurate Cascade classifier is used to recognize faces. Adam is the optimizer, and cross-entropy serves as the loss function. More than 1500 images were used to train the model, which comprises classes with and without masks. The public will start wearing masks in public areas because of the terror that this AI-based mask recognition system instils in them, helping to stop the spread of diseases that are otherwise beneficial to society.
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