استخراج ویژگی نقطه به نقطه تصاویر هوش مصنوعی
ترجمه نشده

استخراج ویژگی نقطه به نقطه تصاویر هوش مصنوعی

عنوان فارسی مقاله: استخراج ویژگی نقطه به نقطه تصاویر هوش مصنوعی بر اساس اینترنت اشیا
عنوان انگلیسی مقاله: Point-by-point feature extraction of artificial intelligence images based on the Internet of Things
مجله/کنفرانس: ارتباطات کامپپیوتری – Computer Communications
رشته های تحصیلی مرتبط: مهندسی کامپیوتر، مهندسی فناوری اطلاعات
گرایش های تحصیلی مرتبط: هوش مصنوعی، اینترنت و شبکه های گسترده
کلمات کلیدی فارسی: اینترنت اشیا، هوش مصنوعی، استخراج ویژگی، تشخیص تصویر
کلمات کلیدی انگلیسی: Internet of Things, Artificial intelligence, Feature extraction, Image detection
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
نمایه: Scopus – Master Journals List – JCR
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.comcom.2020.05.015
دانشگاه: Sichuan University of Media and Communications, Chengdu, China
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2020
ایمپکت فاکتور: 3.886 در سال 2019
شاخص H_index: 98 در سال 2020
شاخص SJR: 0.687 در سال 2019
شناسه ISSN: 0140-3664
شاخص Quartile (چارک): Q1 در سال 2019
فرمت مقاله انگلیسی: PDF
تعداد صفحات مقاله انگلیسی: 8
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
کد محصول: E15092
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست انگلیسی مطالب

Abstract


1- Introduction


2- Design of artificial intelligence image detection system based on Internet of Things


3- Experimental result and analysis


4- Conclusion


References

نمونه متن انگلیسی مقاله

Abstract


In the context of the rapid development of artificial intelligence in the Internet of Things, the establishment of the Internet of Things can promote rapid progress in the field of artificial intelligence. Traditional image detection methods use wavelet energy algorithms to divide background and edge noise, with poor resolution and low image detection accuracy. A series of problems such as slow detection speed and lack of image depth analysis exists. Aiming at the disadvantages of traditional methods, this study proposes the design of an artificial intelligence image detection system based on the Internet of Things, and uses intelligent artificial pixel feature collection technology to extract point-by-point feature of the image. This paper introducing artificial intelligence learning algorithms to the wheel detection in the workshop under the Internet of Things system, which can not only solve the problem of poor feature anti-interference and poor robustness in the traditional method, but also has important significance for the secondary development of the wheel detection system. The neural network can be used to classify wheel images while integrating other detection requirements, such as wheel defect detection and wheel number identification. The rich data resources and processing capabilities of the Internet of Things to perform feature analysis and feedback on the collected image pixels are utilized. The artificial intelligence of image synthesis module performs image conversion processing on the signal processes the feedback signal. The analysis results can complete image detection and complete artificial intelligence images. Through simulation experiments, it is proved that the design of artificial intelligence image detection system based on the Internet of Things has the advantages of high image detection rate, high recognition accuracy, stable operation, and efficient processing. The design idea has good application value.


Introduction


The rapid development of computer and internet technologies has closely linked people, machines, and the internet to form an IoT network with a wealth of data resources and a huge amount of interaction [1,2]. The establishment of the IoT network proves that Internet technology has reached the ability to support cutting-edge technology research and development, such as artificial intelligence. In recent years, artificial intelligence technology has made great progress. Artificial intelligence technology is quietly entering public life, such as drones, medicine, biosecurity and other fields [3]. In many fields, as a special form of data information expression, how to interpret the contained information has been a research problem in the field of image detection. Traditional image detection systems use algorithms such as wavelet to implement image content information detection and detection by dividing the image area and background, and analyzing image noise. This method has a series of problems such as high image clarity requirements, low pixel image recognition and detection accuracy, low accuracy, and poor analysis and processing capabilities [4]. Aiming at the problems existing in the traditional image detection system, based on the Internet of Things and artificial intelligence technology, the design of an artificial intelligence image detection system based on the Internet of Things is proposed. The intelligent artificial pixel feature collection technology extracts point-by-point features of the detected image source and converts them into digital signals to the cloud. It is to use the Internet of Things to enrich data volume resources and processing capabilities, and collect the image pixels of digital signal [5]. The information data is subjected to feature analysis and feedback, and the feedback signal passes through the artificial intelligence signal image synthesis module to perform image conversion processing on the feedback signal and output the analysis result to complete image detection. The current popular Internet of Things technology to achieve organic integration with artificial intelligence technology, a special artificial intelligence image detection system based on the Internet of Things has been proposed [6].

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