Computational Intelligence
Accurate diagnosis of patient conditions becomes challenging for medical practitioners in urban metropolitan cities. A variety of languages and spoken dialects impedes the diagnosis achieved through the exploratory journey a medical practitioner and patient go through. Natural language processing has been used in well-known applications, such as Google Translate, as a solution to reduce language barriers. Languages typically encountered in these applications provide the most known, used or standardized dialect.
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The dataset consists of two classes: COVID-19 cases and Healthy cases
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This dataset consists of 2579 image pairs (5158 images in total) of wood veneers before and after drying. The high-resolution .png images (generally over 4000x4000) have a white background. The data has been collected from a real plywood factory. Raute Corporation is acknowledged for making this dataset public. The manufacturing process is well visualized here: https://www.youtube.com/watch?v=tjkIYCEVXko.
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This dataset has information of 83 patients from India. This dataset contains patients’ clinical history, histopathological features, and mammogram. The distinctive aspect of this dataset lies in its collection of mammograms that have benign tumors and used in subclassification of benign tumors.
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Mother’s Significant Feature (MSF) Dataset has been designed to provide data to researchers working towards woman and child health betterment. MSF dataset records are collected from the Mumbai metropolitan region in Maharashtra, India. Women were interviewed just after childbirth between February 2018 to March 2021. MSF comprise of 450 records with a total of 130 attributes consisting of mother’s features, father’s features and health outcomes. A detailed dataset is created to understand the mother’s features spread across three phases of her reproductive age i.e.
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2148 Views
WITH the advancement in sensor technology, huge amounts of data are being collected from various satellites. Hence, the task of target-based data retrieval and acquisition has become exceedingly challenging. Existing satellites essentially scan a vast overlapping region of the Earth using various sensing techniques, like multi-spectral, hyperspectral, Synthetic Aperture Radar (SAR), video, and compressed sensing, to name a few.
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450 ViewsWITH the advancement in sensor technology, huge amounts of data are being collected from various satellites. Hence, the task of target-based data retrieval and acquisition has become exceedingly challenging. Existing satellites essentially scan a vast overlapping region of the Earth using various sensing techniques, like multi-spectral, hyperspectral, Synthetic Aperture Radar (SAR), video, and compressed sensing, to name a few.
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300 Views
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3345 Views
With the rapid growth of the Bangla music industry huge volume of Bangla songs is produced every day. An immense number of producers, lyricists, singers, and artists are involved in the production of songs from different genres. Among many genres of Bangla music; classical, folk, baul, modern music, Rabindra Sangeet, Nazrul Geeti, film music, rock music, and fusion music have gained the highest popularity. Lyricists try to express their feelings and views towards any situation or subject through their writings.
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In large-scale multi-objective optimization, as the decision space's dimensionality increases, evolutionary algorithms can easily fall into an optimal local state. Therefore, how to prevent the algorithm from falling into a local optimum and quickly converge to the Pareto front is a particularly challenging problem. In order to solve the problem, this paper proposes a grid-based fuzzy evolution large-scale multi-objective optimization framework, which divides the entire evolution process into two main stages: fuzzy evolution and precise evolution.
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