Today, computer vision algorithms are very important for different fields and applications, such as closed-circuit television security, health status monitoring, and recognizing a specific person or object and robotics. Regarding this topic, the present paper deals with a recent review of the literature on computer vision algorithms (recognition and tracking of faces, bodies, and objects) oriented towards socially assistive robot applications. The performance, frames per second (FPS) processing speed, and hardware implemented to run the algorithms are highlighted by comparing the available solutions. Moreover, this paper provides general information for researchers interested in knowing which vision algorithms are available, enabling them to select the one that is most suitable to include in their robotic system applications.
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http://dx.doi.org/10.3390/s21175728 | DOI Listing |
Sci Rep
December 2024
College of Advanced Manufacturing Innovation, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand.
Vector-borne diseases pose a major worldwide health concern, impacting more than 1 billion people globally. Among various blood-feeding arthropods, mosquitoes stand out as the primary carriers of diseases significant in both medical and veterinary fields. Hence, comprehending their distinct role fulfilled by different mosquito types is crucial for efficiently addressing and enhancing control measures against mosquito-transmitted diseases.
View Article and Find Full Text PDFBMC Genomics
December 2024
Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw, 02-106, Poland.
Low Complexity Regions (LCRs) are segments of proteins with a low diversity of amino acid composition. These regions play important roles in proteins. However, annotations describing these functions are dispersed across databases and scientific literature.
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December 2024
Neurology, Icahn School of Medicine at Mount Sinai, New York, USA.
We used machine learning to investigate the residual visual field (VF) deficits and macula retinal ganglion cell (RGC) thickness loss patterns in recovered optic neuritis (ON). We applied archetypal analysis (AA) to 377 same-day pairings of 10-2 VF and optical coherence tomography (OCT) macula images from 93 ON eyes and 70 normal fellow eyes ≥ 90 days after acute ON. We correlated archetype (AT) weights (total weight = 100%) of VFs and total retinal thickness (TRT), inner retinal thickness (IRT), and macular ganglion cell-inner plexiform layer (GCIPL) thickness.
View Article and Find Full Text PDFCell Rep Methods
December 2024
Portrai, Inc., Dongsullagil, 78-18 Jongrogu, Seoul, Republic of Korea; Department of Nuclear Medicine, Seoul National University Hospital, 03080 Seoul, Republic of Korea; Department of Nuclear Medicine, Seoul National University College of Medicine, 03080 Seoul, Republic of Korea. Electronic address:
Spatially resolved transcriptomics (ST) has revolutionized the field of biology by providing a powerful tool for analyzing gene expression in situ. However, current ST methods, particularly barcode-based methods, have limitations in reconstructing high-resolution images from barcodes sparsely distributed in slides. Here, we present SuperST, an algorithm that enables the reconstruction of dense matrices (higher-resolution and non-zero-inflated matrices) from low-resolution ST libraries.
View Article and Find Full Text PDFTomography
December 2024
Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA.
This research introduces BAE-ViT, a specialized vision transformer model developed for bone age estimation (BAE). This model is designed to efficiently merge image and sex data, a capability not present in traditional convolutional neural networks (CNNs). BAE-ViT employs a novel data fusion method to facilitate detailed interactions between visual and non-visual data by tokenizing non-visual information and concatenating all tokens (visual or non-visual) as the input to the model.
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