Zobrazeno 1 - 10
of 389
pro vyhledávání: '"spatiotemporal information"'
Publikováno v:
Taiyuan Ligong Daxue xuebao, Vol 55, Iss 4, Pp 734-742 (2024)
Purposes How to perform bias-correction for precipitation data based on terrain information has been an important problem in meteorological big data research. However, the existing precipitation terrain-based bias-correction methods mostly suffer fro
Externí odkaz:
https://doaj.org/article/ac9fb95f43394ae88a72fc5d3bcc1e33
Autor:
Xiaolong Dong, Xiumian Hu, Wen Lai, Weiwei Xue, Shijie Zhang, Yiqiu Zhang, Wei An, Haiming Fan, Sijin Chen, Cui Li, Xingyun Wang, Yue Wu, Jinlv Chen, Yajun Zhang, Kun Yu
Publikováno v:
Geoscience Data Journal, Vol 11, Iss 2, Pp 128-136 (2024)
Abstract Detrital composition of sandstone is the most important data for siliciclastic studies including sandstone classification, provenance analysis, oil and gas exploration. A large amount of detrital composition data has accumulated over the pas
Externí odkaz:
https://doaj.org/article/1c4b97411f524dbc98010a852aa221ef
Autor:
Siripen Pongpaichet, Boonyapat Sukosit, Chitchaya Duangtanawat, Jiramed Jamjongdamrongkit, Chancheep Mahacharoensuk, Kantapong Matangkarat, Pattadon Singhajan, Thanapon Noraset, Suppawong Tuarob
Publikováno v:
IEEE Access, Vol 12, Pp 22778-22802 (2024)
Crimes result in not only loss to individuals but also hinder national economic growth. While crime rates have been reported to decrease in developed countries, underdeveloped and developing nations still suffer from prevalent crimes, especially thos
Externí odkaz:
https://doaj.org/article/003f2f3b415b41209791d9522f688ce3
Publikováno v:
Geoscience Data Journal, Vol 11, Iss 1, Pp 86-93 (2024)
Abstract As a hot topic in Earth sciences, the Qinghai‐Tibet Plateau has accumulated a large amount of sedimentary‐related data. We constructed a dataset of detrital components for Qinghai‐Tibet Plateau from 63 peer‐reviewed publications. The
Externí odkaz:
https://doaj.org/article/05e29ad23c1d420b919d1aeb191df768
Autor:
Jae-Yeul Kim, Jong-Eun Ha
Publikováno v:
IEEE Access, Vol 11, Pp 145551-145565 (2023)
Visual surveillance requires robust detection of foreground objects under challenging environments of abrupt lighting variation, stationary foreground objects, dynamic background objects, and severe weather conditions. Most classical algorithms lever
Externí odkaz:
https://doaj.org/article/0cee51602ba44baf89c00ab6a86020fe
Autor:
Liying Tao, Pan Li, Meihua Meng, Zonglin Yang, Xiaozhuang Liu, Jinhua Hu, Ji Dong, Shushan Qiao, Tianchun Ye, Delong Shang
Publikováno v:
IEEE Access, Vol 11, Pp 43566-43582 (2023)
Spiking Neural Networks (SNNs), the third generation of artificial neural networks, have been widely employed. However, the realization of advanced artificial intelligence is challenging due to the dearth of efficient spatiotemporal information integ
Externí odkaz:
https://doaj.org/article/89d69bfd70b94b73b8084cf6693d5564
Dynamic Ferroelectric Transistor‐Based Reservoir Computing for Spatiotemporal Information Processing
Publikováno v:
Advanced Intelligent Systems, Vol 5, Iss 6, Pp n/a-n/a (2023)
Reservoir computing (RC) architecture which mimics the human brain is a fundamentally preferred method to process dynamical systems that evolve with time. However, the difficulty in generating rich reservoir states using two‐terminal devices remain
Externí odkaz:
https://doaj.org/article/ca690be3c691498f8ac9f76fd23e937f
Publikováno v:
SmartMat, Vol 4, Iss 2, Pp n/a-n/a (2023)
Abstract A significant step toward constructing high‐efficiency neuromorphic systems is the electronic emulation of advanced synaptic functions of the human brain. While previous studies have focused on mimicking the basic functions of synapses usi
Externí odkaz:
https://doaj.org/article/9a72aa4d0157400b98cbcf4758925a41
Publikováno v:
Applied Sciences, Vol 13, Iss 21, p 11799 (2023)
Due to the limited understanding of the physical and chemical processes involved in ozone formation, as well as the large uncertainties surrounding its precursors, commonly used methods often result in biased predictions. Deep learning, as a powerful
Externí odkaz:
https://doaj.org/article/b1b1582b01fb4d5ba32c6c3fab906532
Publikováno v:
Applied Sciences, Vol 13, Iss 20, p 11183 (2023)
The increasing prevalence of intelligent driving sightseeing vehicles in the tourism industry underscores the critical importance of real-time planning for effective local obstacle avoidance paths when these vehicles encounter obstacles during operat
Externí odkaz:
https://doaj.org/article/3b55125e39604bf7be781d4623ef2d8f