Entirely common sleep disorder is the dangerous wakefulness (Apnea) of breathing during snoring. In this study, we explore the possibility of how medical imageprocessing can be useful and accurate method for sleep di...
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In this article a new data transmission protocol between embedded computers and the fog computing environment for imageprocessing is considered. The possibilities of using fog environment for intelligent processing o...
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ISBN:
(纸本)9781665468282
In this article a new data transmission protocol between embedded computers and the fog computing environment for imageprocessing is considered. The possibilities of using fog environment for intelligent processing of video are revealed. The problems of transmission protocols are indicated. A comparison of existing video processingsystems is given. The place of embedded computers in intelligent video surveillance systems and ways of upgrading these systems are considered. Data from the devices is collected using embedded computers and visualized using IoT technologies. The developed data transmission protocol allows processingimages in the fog and/or cloud for intelligent video surveillance systems. It assumes packet data transmission of series of frames with additional information that are processed using machine learning algorithms and neural networks. The effectiveness of the new systems is shown. As an example, the problem of processing video coming from cameras used in the subway to determine damage of the escalator tape and steps is considered. systems for imageprocessing that implement the proposed protocol can be used not only in the subway, but also in many other areas where Internet of things technologies are supported.
This article presents an algorithm for determining reference brightness correction coefficients to improve image quality. The algorithm utilizes a combination of statistical analysis and imageprocessing techniques to...
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In this work we have presented the approach for the astronomical object recognition and detection of its near-zero motion in the series of images and compressed videos from the "live" (online) data stream us...
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ISBN:
(数字)9781665495783
ISBN:
(纸本)9781665495783
In this work we have presented the approach for the astronomical object recognition and detection of its near-zero motion in the series of images and compressed videos from the "live" (online) data stream using the developed method of in situ modeling. We have described all required preconditions and constants for the method of in situ modeling. The substitutional method implemented on a maximum likelihood criterion and the method implemented on the Fisher f-criterion were selected as the detection algorithms for the near-zero motion of objects for the current research. We have analyzed the several quality indicators of detection of the objects near-zero motion by applying the statistical imitation modeling techniques and using the conditional probability of the true detection.
Player tracking is a useful tool for tactical analysis and performance evaluation in soccer, providing valuable insights into player movements and team dynamics. This project investigates the feasibility of tracking p...
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Integrating deep learning with computer vision technologies and analysing their application efficiency is the main emphasis of this research. Building hierarchical neural networks, a key component of deep learning, al...
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Uncoupled radar networks offer many desired features such as large virtual apertures and flexibility in sensor placement without costly radio frequency (RF) cables. However, they also introduce novel challenges, espec...
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The scientific and methodological foundations for the optimal identification of micro-objects with mechanisms for using information structural components, features, statistical and dynamic characteristics of images ha...
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Real-world databases nowadays are particularly vulnerable to noisy, missing and inconsistent data due to their large size (often several terabytes or so more), as well as the potential that they come from multiple and...
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In the modern industrial context, laser processes, such as laser cutting and laser welding, are predominantly monitored and partially controlled in specific areas, such as process abort scenarios or axis actuator move...
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ISBN:
(纸本)9781510684607;9781510684614
In the modern industrial context, laser processes, such as laser cutting and laser welding, are predominantly monitored and partially controlled in specific areas, such as process abort scenarios or axis actuator movements. Industrial driven interfaces like OPC UA or proprietary bus interface recently allow data acquisition from those control units within certain limits. This data can be augmented with highly accurate scientific data sources. In our proposed setup this is achieved by integrating laser acoustic sensors along with high speed cameras operating in visual and thermal spectrum. The variety of available data sources offers a significant potential for further processing and analysis via artificial intelligence (AI), contributing to deeper process understanding and further development of enhanced control algorithms of laser material machining processes. A post-mortem annotation with quality characteristics such as dross formation, surface roughness, welding depth, porosity, crater formation, etc. deliver all premises to develop and train AI based control models. To link all data sources and annotations a common time management and time normal is required. Its time resolution depends on the fastest cycle time governing a control answer, typically executed in the range of sub milliseconds. A time scale smaller than standard AI algorithms typically deliver complex inference results. Our paper presents an approach to close the time gap by introducing a smart control platform capable of capturing and preprocessing data in real time by utilizing hardware accelerated acquisition algorithms and time management (FPGA-MPSoC). The solution was implemented, transferred to a state of the art welding and cutting setup, and successfully tested. A foundation for an AI controlled laser machining process is set.
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