This paper tackles component identification in hand-drawn electrical circuit diagrams by employing Region-based Convolutional Neural Networks (R-CNN). This paper introduces a new offline circuit recognition system for...
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An understanding of the complex ecosystem in the human gut microbiome is essential in determining the cause of a variety of health conditions including cancer and other diseases. This research establishes an improved ...
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Cloud computing is expanding faster than anticipated;hence, load balancing must be done effectively. Conventional methods like Round Robin and static prioritization tend to struggle under dynamic demand, resulting in ...
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The Fourth Industrial Revolution (4IR) era in Nigeria marks a paradigm shift, driven by technological advancements. Emerging innovations, including artificial intelligence (AI), the Internet of Things (IoT), and autom...
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While highly important for a person's mood, productivity, and physical performance, perceived sleep quality is challenging to model and, thus, predict with passive means such as physiological and behavioral signal...
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Multimodal machine learning(MML)aims to understand the world from multiple related *** has attracted much attention as multimodal data has become increasingly available in real-world *** is shown that MML can perform ...
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Multimodal machine learning(MML)aims to understand the world from multiple related *** has attracted much attention as multimodal data has become increasingly available in real-world *** is shown that MML can perform better than single-modal machine learning,since multi-modalities containing more information which could complement each ***,it is a key challenge to fuse the multi-modalities in *** from previous work,we further consider the side-information,which reflects the situation and influences the fusion of *** recover multimodal label distribution(MLD)by leveraging the side-information,representing the degree to which each modality contributes to describing the ***,a novel framework named multimodal label distribution learning(MLDL)is proposed to recover the MLD,and fuse the multimodalities with its guidance to learn an in-depth understanding of the jointly feature ***,two versions of MLDL are proposed to deal with the sequential *** on multimodal sentiment analysis and disease prediction show that the proposed approaches perform favorably against state-of-the-art methods.
While local competitiveness is an essential measure in evaluating localities’ performance, it is cumbersome due to the inclusion of numerous indicators. This study proposes an unsupervised feature selection method ba...
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In this work, we aim to evaluate the performance of Machine Learning models in the classification of Alzheimer's patients into disease stages using two feature selection methods proposed in our previous work. The ...
This research paper uses historical data from Ambuja Cement to compare nine machine learning algorithms for algorithmic trading in the Indian stock market. The algorithms applied include SVM, Linear Regression, Decisi...
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Kyphosis, characterized by the inward arching of the upper back, is often colloquially referred to as 'roundback' or 'hunchback' when a noticeable curvature is present. This condition typically arises ...
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