Coronavirus(COVID-19)outbreak was first identified in Wuhan,China in December *** was tagged as a pandemic soon by the WHO being a serious public medical *** spite of the fact that the virus can be diagnosed by qRT-PC...
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Coronavirus(COVID-19)outbreak was first identified in Wuhan,China in December *** was tagged as a pandemic soon by the WHO being a serious public medical *** spite of the fact that the virus can be diagnosed by qRT-PCR,COVID-19 patients who are affected with pneumonia and other severe complications can only be diagnosed with the help of Chest X-Ray(CXR)and Computed Tomography(CT)*** this paper,the researchers propose to detect the presence of COVID-19 through images using Best deep learning model with various *** features like Speeded-Up Robust Features(SURF),Features from Accelerated Segment Test(FAST)and Scale-Invariant Feature Transform(SIFT)are used in the test images to detect the presence of *** optimal features are extracted from the images utilizing DeVGGCovNet(Deep optimal VGG16)model through optimal learning *** task is accomplished by exceptional mating conduct of Black Widow *** this strategy,cannibalism is *** this phase,fitness outcomes are rejected and are not satisfied by the proposed *** results acquired from real case analysis demonstrate the viability of DeVGGCovNet technique in settling true issues using obscure and testing ***16 model identifies the imagewhich has a place with which it is dependent on the distinctions in *** impact of the distinctions on labels during training stage is studied and predicted for test *** proposed model was compared with existing state-of-the-art models and the results from the proposed model for disarray grid estimates like Sen,Spec,Accuracy and F1 score were promising.
The lighting conditions at the environment are not favorable for imaging, and the problem of light is one of the challenges of imaging in the environment. The lack of sufficient light in the images reduces the quality...
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Breast cancer is a leading cause of cancer-related deaths globally, necessitating effective diagnostic measures. Tissue biopsy examination and histopathology image analysis are pivotal in clinical cancer diagnosis. Va...
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A key facilitating infrastructure for building intelligent structures that enable efficient in-person and virtual learning environments is the Internet of Things (IoT). The shift to smart learning, that includes IoT a...
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Teaching students complex problem-solving skills using large-scale, real-world problems is challenging for both students and teachers alike. As a result, most courses use small, well-specified, toy-like problems, whic...
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Unmanned aerial vehicles (UAVs) rely on optical sensors such as cameras and lidar for autonomous operation. However, such optical sensors are error-prone in bad lighting, inclement weather conditions including fog and...
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High-utility itemset mining(HUIM)can consider not only the profit factor but also the profitable factor,which is an essential task in data ***,most HUIM algorithms are mainly developed on a single machine,which is ine...
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High-utility itemset mining(HUIM)can consider not only the profit factor but also the profitable factor,which is an essential task in data ***,most HUIM algorithms are mainly developed on a single machine,which is inefficient for big data since limited memory and processing capacities are available.A parallel efficient high-utility itemset mining(P-EFIM)algorithm is proposed based on the Hadoop platform to solve this problem in this *** P-EFIM,the transaction-weighted utilization values are calculated and ordered for the itemsets with the MapReduce *** the ordered itemsets are renumbered,and the low-utility itemsets are pruned to improve the dataset *** the Map phase,the P-EFIM algorithm divides the task into multiple independent *** uses the proposed S-style distribution strategy to distribute the subtasks evenly across all nodes to ensure ***,the P-EFIM uses the EFIM algorithm to mine each subtask dataset to enhance the performance in the Reduce *** are performed on eight datasets,and the results show that the runtime performance of P-EFIM is significantly higher than that of the PHUI-Growth,which is also HUIM algorithm based on the Hadoop framework.
The aim of this article is to present a survey on Machine Learning approaches for performing water analysis as in general integrating Artificial Intelligence in water analysis has a transformative potential for optimi...
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In some real-world data sets, there is a class imbalance where one class (the minority class) has a limited number of data points and the other class (the dominant class) has a large number of data points. With the st...
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To enable large-scale and efficient deployment of artificial intelligence (AI), the combination of AI and edge computing has spawned Edge Intelligence, which leverages the computing and communication capabilities of e...
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