Journal ArticleDOI
Moving target recognition with seismic sensing: A review
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A comprehensive survey on moving target recognition with the IoGN is conducted, including two representative types of seismic sensors and corresponding data acquisition units, and systematically summarize the detection and classification algorithms for target recognition.About:
This article is published in Measurement.The article was published on 2021-08-01. It has received 9 citations till now.read more
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Journal ArticleDOI
Deep-learning seismology
TL;DR: A comprehensive review of the deep learning techniques being applied to seismic datasets, covering approaches, limitations, and opportunities is provided by Mousavi and Beroza as mentioned in this paper , who present a systematic overview of trends, challenges and opportunities in applications of deep learning methods in seismology.
Journal ArticleDOI
A Target Recognition Algorithm of Multi-Source Remote Sensing Image Based on Visual Internet of Things
Xueming Sun,Chun Wei Lin +1 more
TL;DR: In this article , the target recognition algorithm of multi-source remote sensing image based on IoT vision is investigated, where the infrared sensor and SAR radars are set in the visual perception layer of the iVIOT.
Journal ArticleDOI
A Target Recognition Algorithm of Multi-Source Remote Sensing Image Based on Visual Internet of Things
Xueming Sun,Jerry Chun-Wei Lin +1 more
TL;DR: In this paper , the target recognition algorithm of multi-source remote sensing image based on IoT vision is investigated, where the infrared sensor and SAR radars are set in the visual perception layer of the iVIOT.
Journal ArticleDOI
Dynamic-transmission-based recursive filtering algorithm for microseismic event detection under sensor saturations
TL;DR: A filter is designed such that the arrival time of P wave and S wave of microseismic signals is picked automatically in consideration of the SS and the DTM, and an upper bound of the filtering error covariance matrix is optimized by the designed filter gain at each time instant.
Journal ArticleDOI
Self-Powered Long-Life Microsystem for Vibration Sensing and Target Recognition
TL;DR: In this article , a low-power, long-life micro-system that integrates self-power supply, event wake-up, continuous vibration sensing, and target recognition is presented.
References
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Deep learning
TL;DR: Deep learning is making major advances in solving problems that have resisted the best attempts of the artificial intelligence community for many years, and will have many more successes in the near future because it requires very little engineering by hand and can easily take advantage of increases in the amount of available computation and data.
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Deep Learning
TL;DR: Deep learning as mentioned in this paper is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts, and it is used in many applications such as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames.
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Compressed sensing
TL;DR: It is possible to design n=O(Nlog(m)) nonadaptive measurements allowing reconstruction with accuracy comparable to that attainable with direct knowledge of the N most important coefficients, and a good approximation to those N important coefficients is extracted from the n measurements by solving a linear program-Basis Pursuit in signal processing.
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Edge Computing: Vision and Challenges
TL;DR: The definition of edge computing is introduced, followed by several case studies, ranging from cloud offloading to smart home and city, as well as collaborative edge to materialize the concept of edge Computing.
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Internet of Things for Smart Cities
TL;DR: This paper will present and discuss the technical solutions and best-practice guidelines adopted in the Padova Smart City project, a proof-of-concept deployment of an IoT island in the city of Padova, Italy, performed in collaboration with the city municipality.