As the number of possibilities for WSNs progressively grows, more people are trying to address the issues that are limiting their growth in the form of two main significant power consumption and delay. The principal s...
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Lung and colon cancers are significant health issues across the world, prompting the need for inventive methods of diagnosis. This study takes the lead in introducing advanced Deep ConvNets (CNNs) to enhance the accur...
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The objective of this study is to examine the effectiveness of a hybrid methodology that combines Long Short-Term Memory (LSTM) and k-Nearest Neighbors (k-NN) models in the context of energy prediction within data cen...
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Fire is the major disaster worldwide, and even worst condition at the village. Hence, the fire detection system or alarm should accurately locate the fire in the shortest amount of time to reduce financial loss and en...
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The objective of content-based image retrieval (CBIR) is to locate and retrieve similar images from the large-scale dataset for a given query image. A conventional CBIR system involves feature extraction, similarity m...
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Electrocardiogram (ECG) signals play a very important role in the detection of heart irregularities. Early detection of abnormalities is essential for better patient care and improved medical outcomes. Recent years ha...
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Enhancing the Bitcoin cost prediction to improve accuracy using a decision tree in comparison with Lasso regression. For trend confirmations, we often utilize the financial phrases support and resistance to the predic...
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Since the coronavirus epidemic has reached every corner of the globe, we need to develop machine-based solutions to detect it. The global spread of novel coronaviruses has claimed millions of lives and prompted the de...
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Moving target detection is one of the most basic tasks in computer *** conventional wisdom,the problem is solved by iterative optimization under either Matrix Decomposition(MD)or Matrix Factorization(MF)*** utilizes f...
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Moving target detection is one of the most basic tasks in computer *** conventional wisdom,the problem is solved by iterative optimization under either Matrix Decomposition(MD)or Matrix Factorization(MF)*** utilizes foreground information to facilitate background *** uses noise-based weights to fine-tune the *** both noise and foreground information contribute to the recovery of the *** jointly exploit their advantages,inspired by two framework complementary characteristics,we propose to simultaneously exploit the advantages of these two optimizing approaches in a unified framework called Joint Matrix Decomposition and Factorization(JMDF).To improve background extraction,a fuzzy factorization is *** fuzzy membership of the background/foreground association is calculated during the factorization process to distinguish their contributions of both to background *** describe the spatio-temporal continuity of foreground more accurately,we propose to incorporate the first order temporal difference into the group sparsity constraint *** temporal constraint is adjusted *** foreground and the background are jointly estimated through an effective alternate optimization process,and the noise can be modeled with the specific probability *** experimental results of vast real videos illustrate the effectiveness of our *** with the current state-of-the-art technology,our method can usually form the clearer background and extract the more accurate ***-noise experiments show the noise robustness of our method.
It is well known that the human factor still plays a significant role in security incidents as malicious actors exploit vulnerabilities in the human dimension of the attack surface to successfully carry out their atta...
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