Artificial Intelligence

— Medical image segmentation is a crucial aspect of medical image processing, and has been widely used in the detection and clinical diagnosis for brain, lung, liver, heart and other diseases. In this paper, we propose a novel multimodal mutual attention network, called MMAUNet, for medical image segmentation. MMA-UNet is divided into two parts. The first part obtains more highdimensional features by skip connection and improved network structure.

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Optical coherence tomography (OCT) is a non-invasive imaging technique that has extensive clinical applications in ophthalmology. OCT enables the visualization of the retinal layers, playing a vital role in the early detection and monitoring of retinal diseases.

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The data set is collected from volunteers from Beijing University Third Hospital. FootScan plantar pressure measurement system is used to record the continuous pressure information. The volunteer is familiar with the whole walking process and is asked to walk on the plate with an order of "left foot, right foot, and then left foot," using comfortable walking speed. Volunteers should always ensure the heel touches the plate before the toe during walking. The sampling frequency of the system is set as 126Hz.

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BENELUX Region of Interest (ROI) , comprised of the Belgium, the Netherlands and Luxembourg

We use the communes administrative division which is standardized across Europe by EUROSTAT at:
https://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/administrative-units-statistical-units
This is roughly equivalent to the notion municipalities in most countries.

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Smart homes contain programmable electronic devices (mostly IoT) that enable home automation. People who live in smart homes benefit from interconnected devices by controlling them either remotely or manually/autonomously. However, high interconnectivity comes with an increased attack surface, making the smart home an attractive target for adversaries. NCC Group and the Global Cyber Alliance recorded over 12,000 attacks to log into smart home devices maliciously. Recent statistics show that over 200 million smart homes can be subjected to these attacks.

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Around from 12th century MODI script was used to write Indian languages as Marathi, Hindi, and Gujarati etc.  It was used as administrative script from 17th century to mid of 19th century in Maharashtra state (India). At present, MODI script users are diminishing away, and countable persons can understand the MODI script. The preserved archaic historical MODI handwritten documents contained important and rare cultural, historic, and administrative kind of information which is usable in present-days.

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MODI script was used to write Indian languages as Marathi, Hindi, and Gujarati etc. from 12th century. From 17th century to mid of 19th century MODI was used as administrative script in Maharashtra state (India). Now a days, MODI script users are diminishing away, and countable persons can understand the MODI script. The archaic historical MODI handwritten documents contained important and rare cultural, historic, and administrative type of information which is usable in current era.

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554 Views

On the basis of autonomous mobile tea picking robot, aiming at the shortcomings of traditional tea bud identification methods such as slow speed, low accuracy and poor adaptability, as well as people's demand for high-quality tea, the research and experiment of tea bud quality classification recognition based on YOLOv5 were carried out. Through the construction of the autonomous mobile tea picking robot visual recognition system, the data set was constructed, which mainly included tea image acquisition, enhancement and annotation.

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699 Views

On the basis of autonomous mobile tea picking robot, aiming at the shortcomings of traditional tea bud identification methods such as slow speed, low accuracy and poor adaptability, as well as people's demand for high-quality tea, the research and experiment of tea bud quality classification recognition based on YOLOv5 were carried out. Through the construction of the autonomous mobile tea picking robot visual recognition system, the data set was constructed, which mainly included tea image acquisition, enhancement and annotation.

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This experiment was implemented to collect infrared images of the coal and gangue samples at the temperature of 323.15 K. Additionally, it showed that distinguishing between coal and gangue samples is feasible, although the area, thickness, and surface conditions were changed at a constant temperature during the process of capturing the infrared images. The coal and gangue were randomly collected from the same mine. The random samples had different weights, shapes, areas, thicknesses, and surface conations. 

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