ARCHITECTURE RECOGNITION BY MEANS OF CONVOLUTIONAL NEURAL NETWORKS

被引：2

作者：

Andrianaivo, Louis N. ^{[1
,2
]}

D'Autilia, Roberto ^{[2
]}

Palma, Valerio ^{[1
]}

机构：

[1] Politecn Torino, FULL, Via Agostino da Montefeltro 2, I-10134 Turin, Italy

[2] Univ Roma Tre, Dipartimento Matemat & Fis, Largo San Leonardo Murialdo 1, I-00146 Rome, Italy

来源：

27TH CIPA INTERNATIONAL SYMPOSIUM: DOCUMENTING THE PAST FOR A BETTER FUTURE | 2019年 / 42-2卷 / W15期

关键词：

Artificial Intelligence; Machine Learning; Deep Learning; Convolutional Neural Networks; Image Classification; Architectural Heritage; Mobile Computing; DEEP;

D O I：

10.5194/isprs-archives-XLII-2-W15-77-2019

中图分类号：

K85 [文物考古];

学科分类号：

0601 ;

摘要：

The use of mobile computing technologies can change the experience of visiting cultural sites by making vast digital heritage collections accessible on site. The spread of machine learning technologies on mobile devices is encouraging the interaction of artificial intelligence with the shape of the built environment. However, while some research already applies deep learning image recognition in an urban context, the literature on how to develop effective neural networks to detect architectural features is still limited, as well as the availability of architecture-related datasets. This work presents the steps and results of the prototype development of a mobile app to perform monument recognition using convolutional neural networks. The tool allows users to interact with the physical space and access a digital archive of texts, models, images and other data.

引用

页码：77 / 84

页数：8

共 50 条

[21] Recognition of Assembly Parts by Convolutional Neural Networks
Zidek, Kamil
Hosovsky, Alexander
Pitel', Jan
Bednar, Slavomir
ADVANCES IN MANUFACTURING ENGINEERING AND MATERIALS, ICMEM 2018, 2019, : 281 - 289
[22] Tactile Motion Recognition with Convolutional Neural Networks
Wu, Haoying
Jiang, Daimin
Gao, Hao
2017 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2017, : 1572 - 1577
[23] Ensemble Convolutional Neural Networks for Face Recognition
Cheng, Wen-Chang
Wu, Tin-Yu
Li, Dai-Wei
2018 INTERNATIONAL CONFERENCE ON ALGORITHMS, COMPUTING AND ARTIFICIAL INTELLIGENCE (ACAI 2018), 2018,
[24] Emotion Recognition in Horses with Convolutional Neural Networks
Corujo, Luis A.
Kieson, Emily
Schloesser, Timo
Gloor, Peter A.
FUTURE INTERNET, 2021, 13 (10):
[25] Driving posture recognition by convolutional neural networks
Yan, Chao
Coenen, Frans
Zhang, Bailing
IET COMPUTER VISION, 2016, 10 (02) : 103 - 114
[26] Ensemble of Convolutional Neural Networks for Face Recognition
Mohanraj, V.
Chakkaravarthy, S. Sibi
Vaidehi, V.
RECENT DEVELOPMENTS IN MACHINE LEARNING AND DATA ANALYTICS, 2019, 740 : 467 - 477
[27] An Analysis of Convolutional Neural Networks for Image Recognition
He, Jun
Liu, Yue
Li, Shuai
Shen, Jin-ming
2017 2ND INTERNATIONAL CONFERENCE ON COMPUTATIONAL MODELING, SIMULATION AND APPLIED MATHEMATICS (CMSAM), 2017, : 524 - 528
[28] Convolutional neural networks for ship type recognition
Rainey, Katie
Reeder, John D.
Corelli, Alexander G.
AUTOMATIC TARGET RECOGNITION XXVI, 2016, 9844
[29] GAIT RECOGNITION BASED ON CONVOLUTIONAL NEURAL NETWORKS
Sokolova, A.
Konushin, A.
INTERNATIONAL WORKSHOP PHOTOGRAMMETRIC AND COMPUTER VISION TECHNIQUES FOR VIDEO SURVEILLANCE, BIOMETRICS AND BIOMEDICINE, 2017, 42-2 (W4): : 207 - 212
[30] TOWARD AIRCRAFT RECOGNITION WITH CONVOLUTIONAL NEURAL NETWORKS
Mash, Robert
Becherer, Nicholas
Woolley, Brian
Pecarina, John
PROCEEDINGS OF THE 2016 IEEE NATIONAL AEROSPACE AND ELECTRONICS CONFERENCE (NAECON) AND OHIO INNOVATION SUMMIT (OIS), 2016, : 225 - 232

← 1 2 3 4 5 →