Zobrazeno 1 - 10
of 11 519
pro vyhledávání: '"mapping framework"'
Ensuring thermal comfort is essential for the well-being and productivity of individuals in built environments. Of the various thermal comfort indicators, the mean radiant temperature (MRT) is very challenging to measure. Most common measurement meth
Externí odkaz:
http://arxiv.org/abs/2410.09443
This document presents a framework for lidar-inertial localisation and mapping named 2Fast-2Lamaa. The method revolves around two main steps which are the inertial-aided undistortion of the lidar data and the scan-to-map registration using a distance
Externí odkaz:
http://arxiv.org/abs/2410.05433
Processing in-memory (PIM) is promising to accelerate neural networks (NNs) because it minimizes data movement and provides large computational parallelism. Similar to machine learning accelerators, application mapping, which determines the operation
Externí odkaz:
http://arxiv.org/abs/2407.00604
Despite the great development of multirobot technologies, efficiently and collaboratively exploring an unknown environment is still a big challenge. In this paper, we propose AIM-Mapping, a Asymmetric InforMation Enhanced Mapping framework. The frame
Externí odkaz:
http://arxiv.org/abs/2404.18089
Autor:
Sarigai, Sarigai, Yang, Liping, Slack, Katie, Lane, K. Maria D., Buenemann, Michaela, Wu, Qiusheng, Woodhull, Gordon, Driscol, Joshua
We are surrounded by overwhelming big data, which brings substantial advances but meanwhile poses many challenges. Geospatial big data comprises a big portion of big data, and is essential and powerful for decision-making if being utilized strategica
Externí odkaz:
http://arxiv.org/abs/2402.11001
Autor:
Shah Heydari, Shahriar1 (AUTHOR) shahriar.shah_heydari@colostate.edu, Vogeler, Jody C.1 (AUTHOR) jody.vogeler@colostate.edu, Cardenas-Ritzert, Orion S. E.1 (AUTHOR) steven.filippelli@colostate.edu, Filippelli, Steven K.1 (AUTHOR), McHale, Melissa2 (AUTHOR) melissa.mchale@ubc.ca, Laituri, Melinda3 (AUTHOR) melinda.laituri@colostate.edu
Publikováno v:
Remote Sensing. Jul2024, Vol. 16 Issue 14, p2677. 53p.
Autor:
Zhu, Hongbo1,2 (AUTHOR) zhb999322@stumail.nciae.edu.cn, Yu, Tao1 (AUTHOR), Mi, Xiaofei1 (AUTHOR) mixf@aircas.ac.cn, Yang, Jian1 (AUTHOR), Tian, Chuanzhao2 (AUTHOR), Liu, Peizhuo1,3 (AUTHOR), Yan, Jian1 (AUTHOR), Meng, Yuke4 (AUTHOR), Jiang, Zhenzhao4 (AUTHOR), Ma, Zhigao4 (AUTHOR)
Publikováno v:
Remote Sensing. Jul2024, Vol. 16 Issue 13, p2443. 19p.
We propose LatentSwap, a simple face swapping framework generating a face swap latent code of a given generator. Utilizing randomly sampled latent codes, our framework is light and does not require datasets besides employing the pre-trained models, w
Externí odkaz:
http://arxiv.org/abs/2402.18351
Autor:
Lin, Yu-Zheng, Mamun, Muntasir, Chowdhury, Muhtasim Alam, Cai, Shuyu, Zhu, Mingyu, Latibari, Banafsheh Saber, Gubbi, Kevin Immanuel, Bavarsad, Najmeh Nazari, Caputo, Arjun, Sasan, Avesta, Homayoun, Houman, Rafatirad, Setareh, Satam, Pratik, Salehi, Soheil
The escalating complexity of modern computing frameworks has resulted in a surge in the cybersecurity vulnerabilities reported to the National Vulnerability Database (NVD) by practitioners. Despite the fact that the stature of NVD is one of the most
Externí odkaz:
http://arxiv.org/abs/2312.13530
Autor:
Schade, Katrin
Publikováno v:
Erdkunde, 2023 Apr 01. 77(2), 127-148.
Externí odkaz:
https://www.jstor.org/stable/27225854