Zobrazeno 1 - 10
of 316
pro vyhledávání: '"embedded platform"'
Publikováno v:
Automatika, Vol 65, Iss 3, Pp 1044-1058 (2024)
This paper presents a novel, cost-effective multisensory system designed for animal monitoring in research settings. The system aims to objectively assess animal welfare and discomfort during experiments, addressing the need for affordable monitoring
Externí odkaz:
https://doaj.org/article/acaf0e4342ed4d54a032d061cd107d5d
Autor:
Liu Yang
Publikováno v:
Measurement: Sensors, Vol 33, Iss , Pp 101120- (2024)
At present, the application of Artificial Intelligence (AI) in industrial control, smart home and other fields has received good response. However, AI technology has certain requirements for computer performance, and also faces problems in network se
Externí odkaz:
https://doaj.org/article/dead431c4bb843c4a0a5d73c28c74b91
Publikováno v:
IEEE Access, Vol 11, Pp 52812-52823 (2023)
The success of research using convolutional neural network (CNN)-based camera sensor processing for autonomous driving has accelerated the development of autonomous driving vehicles. Since autonomous driving algorithms require high-performance comput
Externí odkaz:
https://doaj.org/article/4afaf58e4898418fa9e7706b9746d753
Publikováno v:
网络与信息安全学报, Vol 8, Pp 29-38 (2022)
With the development of wireless communication technology and the popularization of intelligent terminals, more and more cryptographic algorithms are applied to IoT devices to ensure the security of communication and data.Among them, the SM2 elliptic
Externí odkaz:
https://doaj.org/article/3613f5171de34e258c347b5cc5f5259b
Publikováno v:
International Journal of Crowd Science, Vol 6, Iss 4, Pp 159-166 (2022)
In a video game review, the main focus is the narratives, characters, graphics, and mechanics in the gameplay. Some recent research mentions the user interface only when it comes into light as a creative platform for simple interactive narratives fro
Externí odkaz:
https://doaj.org/article/ea4fe0b9bb05458e8b0e4375a3229dd6
Autor:
Micaela Troglia Gamba, Brendan David Polidori, Alex Minetto, Fabio Dovis, Emilio Banfi, Fabrizio Dominici
Publikováno v:
Sensors, Vol 24, Iss 2, p 508 (2024)
The disruptive effect of radio frequency interference (RFI) on global navigation satellite system (GNSS) signals is well known, and in the last four decades, many have been investigated as countermeasures. Recently, low-Earth orbit (LEO) satellites h
Externí odkaz:
https://doaj.org/article/c7c23b6e089c42ce9ce0e82e55d3f5af
Publikováno v:
Sensors, Vol 23, Iss 24, p 9689 (2023)
Indoor fires pose significant threats in terms of casualties and economic losses globally. Thus, it is vital to accurately detect indoor fires at an early stage. To improve the accuracy of indoor fire detection for the resource-constrained embedded p
Externí odkaz:
https://doaj.org/article/8bd28e0296cc4d7593b11f5ab48071fe
Publikováno v:
Agriculture, Vol 13, Iss 11, p 2144 (2023)
Cassava (Manihot esculenta Crantz) is a major tuber crop worldwide, but its mechanized harvesting is inefficient. The digging–pulling cassava harvester is the primary development direction of the cassava harvester. However, the harvester clamping
Externí odkaz:
https://doaj.org/article/0a284080ed914f3491c859c9e2bc90d1
A Novel Lightweight Object Detection Network with Attention Modules and Hierarchical Feature Pyramid
Publikováno v:
Symmetry, Vol 15, Iss 11, p 2080 (2023)
Object detection methods based on deep learning typically require devices with ample computing capabilities, which limits their deployment in restricted environments such as those with embedded devices. To address this challenge, we propose Mini-YOLO
Externí odkaz:
https://doaj.org/article/659b999a8b1d41c88f33441366df61d2
Publikováno v:
Mathematics, Vol 11, Iss 20, p 4276 (2023)
A launch vehicle needs to adapt to a complex flight environment during flight, and traditional guidance and control algorithms can hardly deal with multi-factor uncertainties due to the high dependency on control models. To solve this problem, this p
Externí odkaz:
https://doaj.org/article/d158ab531d7847f1a2f193e05158f33c