Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Huanhuan Ran"'
Publikováno v:
npj Climate and Atmospheric Science, Vol 7, Iss 1, Pp 1-9 (2024)
Abstract In August 2022, unprecedented and long-lasting extreme heatwaves attacked the Northern Hemisphere, with simultaneous record-breaking surface air temperature (SAT) in Eastern Europe (EE), Southern China (SC), and Western North America (WNA).
Externí odkaz:
https://doaj.org/article/07463b77e14c4873a31809a89d39b94a
Aiming at the problems of small speed and large memory resource consumption for aerial images got by Unmanned Aerial Vehicle (UAV), which caused by the high pixel, high precision and large size, a real-time image stitching method integrating feature
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7ba28c2f5cfa6c5632c1beb64c2b1f15
https://doi.org/10.22541/au.168084186.64640770/v1
https://doi.org/10.22541/au.168084186.64640770/v1
Autor:
Yunfeng Ma, Shan Yan, Huanhuan Ran, Shiping Wen, Kaibo Shi, Shu Cheng, Shunkai Meng, Liang Sun
Publikováno v:
Asian Journal of Control. 24:510-516
Searching for a distinguishable lost target in a bounded area automatically with unmanned aerial vehicle (UAV) is a fundamental problem in the theory of physical search. This paper studies the problem in detail, presents a new and more realistic Baye
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6fd4471411fe78dad5d494b8ab3a5051
https://doi.org/10.1002/asjc.2517
https://doi.org/10.1002/asjc.2517
Autor:
Qian Li, Shiping Wen, Yuming Feng, Yin Yang, Kaibo Shi, Huanhuan Ran, Tingwen Huang, Pan Zhou
In this article, a novel edge computing system is proposed for image recognition via memristor-based blaze block circuit, which includes a memristive convolutional neural network (MCNN) layer, two single-memristive blaze blocks (SMBBs), four double-m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::55cc729fb0350e462bb262513f5bb32c
https://hdl.handle.net/10453/166552
https://hdl.handle.net/10453/166552
Publikováno v:
IEEE transactions on neural networks and learning systems.
As edge computing platforms need low power consumption and small volume circuit with artificial intelligence (AI), we design a compact and stable memristive visual geometry group (MVGG) neural network for image classification. According to characteri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bd096a54385b531dcc461451e0e53a0a
https://pubmed.ncbi.nlm.nih.gov/34464264
https://pubmed.ncbi.nlm.nih.gov/34464264
According to the requirements of edge intelligence for circuit volume, power consumption and computing performance, a Memristive GoogLeNet Neural Network (MGNN) circuit is designed using memristor which is a new device integrating storage and computi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a060b06b043b2f4a5001484a4ecb1a38
https://hdl.handle.net/10453/157630
https://hdl.handle.net/10453/157630
In this article, we propose a memristor-based ShuffleNetV2 for image classification. Because of the low power consumption and high integration, this circuit is suitable for edge computing. The memristor-based ShuffleNetV2 is divided into four kinds o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c4289caab97dc004f1bd25c5ce7f220c
https://hdl.handle.net/10453/156646
https://hdl.handle.net/10453/156646
Autor:
Huanhuan Ran, Zili Huang
Publikováno v:
Journal of Computer Applications. 33:57-60
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e2862ae9f5d76a6a3d61c58ae34b456d
https://doi.org/10.3724/sp.j.1087.2013.00057
https://doi.org/10.3724/sp.j.1087.2013.00057
Publikováno v:
SPIE Proceedings.
For reducing the error of affine transform while matching the three-dimensional targets in optical images, the model of optical images matching was extended to three dimension using distance information of high characteristics in optical images (vect
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::de3d5d3d51c7f43da37e74fbc7bc0caa
https://doi.org/10.1117/12.2064970
https://doi.org/10.1117/12.2064970