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Wyszukujesz frazę "OpenCv" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
Application of the OpenCV library in indoor hydroponic plantations for automatic height assessment of plants
Autorzy:
Pietrzykowski, Sławomir Krzysztof
Wymysłowski, Artur
Powiązania:
https://bibliotekanauki.pl/articles/27314190.pdf
Data publikacji:
2022
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
hydroponics
image analysis
automatics
mechatronic system
opencv
phenotyping
Opis:
This paper presents a method for automatically measuring plants’ heights in indoor hydroponic plantations using the OpenCV library and the Python programming language. Using the elaborated algorithm and Raspberry Pi-driven system with an external camera, the growth process of multiple pak choi cabbages (Brassica rapa L. subsp. Chinensis) was observed. The main aim and novelty of the presented research is the elaborated algorithm, which allows for observing the plants’ height in hydroponic stations, where reflective foil is used. Based on the pictures of the hydroponic plantation, the bases of the plants, their reflections, and plants themselves were separated. Finally, the algorithm was used for estimating the plants’ heights. The achieved results were then compared to the results obtained manually. With the help of a ML (Machine Learning) approach, the algorithm will be used in future research to optimize the plants’ growth in indoor hydroponic plantations.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2022, 16, 2; 55--63
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Integrated and deep learning–based social surveillance system : a novel approach
Autorzy:
Litoriya, Ratnesh
Ramchandani, Dev
Moyal, Dhruvansh
Bothra, Dhruv
Powiązania:
https://bibliotekanauki.pl/articles/27314204.pdf
Data publikacji:
2022
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
Video Surveillance
object detection
object tracking
YOLO v4 algorithm
OpenCV
Opis:
In industry and research, big data applications are gaining a lot of traction and space. Surveillance videos contribute significantly to big unlabelled data. The aim of visual surveillance is to understand and determine object behavior. It includes static and moving object detection, as well as video tracking to comprehend scene events. Object detection algorithms may be used to identify items in any video scene. Any video surveillance system faces a significant challenge in detecting moving objects and differentiating between objects with same shapes or features. The primary goal of this work is to provide an integrated framework for quick overview of video analysis utilizing deep learning algorithms to detect suspicious activity. In greater applications, the detection method is utilized to determine the region where items are available and the form of objects in each frame. This video analysis also aids in the attainment of security. Security may be characterized in a variety of ways, such as identifying theft or violation of covid protocols. The obtained results are encouraging and superior to existing solutions with 97% accuracy.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2022, 16, 3; 30--39
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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