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Problems In Indoor Mapping and Modelling

S. Zlatanova, G. Sithole, M. Nakagawa, Q. Zhu • The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2013)

Research in support of indoor mapping and modelling (IMM) has been active for over thirty years. This research has come in the form of As-Built surveys, Data structuring, Visualisation techniques, Navigation models and so forth. Much of thi...

DOAJ Open Access (DOAJ) DOI: 10.5194/isprsarchives-XL-4-W4-63-2013

Evaluation of Modified FGSM-Based Data Augmentation Method for Convolutional Neural Network-Based Image Classification

Paulo Monteiro de Carvalho Monson, Vinicius Augusto Dare de Almeida, Gabriel Augusto David, Pedro Oliveira Conceição Junior et al. • Engineering Proceedings (2024)

Computer vision applications demand a significant amount of data for effective training and inference in many computer vision tasks. However, data insufficiency situations usually happen due to multiple reasons, resulting in computational m...

DOAJ Open Access (DOAJ) DOI: 10.3390/ecsa-11-20476

Enhanced Combined Techniques for Interval-Valued Intuitionistic Fuzzy Multiple-Attribute Group Decision-Making and Applications to Quality Evaluation of Large-Scale Multi-View 3D Reconstruction

Longpeng Bian, Chang Che • IEEE Access (2023)

With the widespread application of computer vision in many fields, quickly and accurately obtaining the three-dimensional information covered by the target object has become a concern in the field of vision research. Large scale multi view ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2023.3327310

Monitoring pedestrian walking dynamics under environmental and policy influences in urban spaces

Mohamed A. Abdelwahab, Shizuo Kaji, Maiya Hori, Shigeru Takano • Computational Urban Science (2026)

Abstract Understanding how environmental conditions and policy interventions jointly shape pedestrian mobility is essential for designing resilient, adaptive, and human-centered urban spaces. This study presents a computer-vision framework ...

DOAJ Open Access (DOAJ) DOI: 10.1007/s43762-026-00284-3

A Comprehensive Review on 3D Object Detection and 6D Pose Estimation With Deep Learning

Sabera Hoque, Md. Yasir Arafat, Shuxiang Xu, Ananda Maiti et al. • IEEE Access (2021)

Nowadays, computer vision with 3D (dimension) object detection and 6D (degree of freedom) pose assumptions are widely discussed and studied in the field. In the 3D object detection process, classifications are centered on the object’...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2021.3114399

DEEP LEARNING-BASED DOOR AND WINDOW DETECTION FROM BUILDING FAÇADE

G. Sezen, M. Cakir, M. E. Atik, Z. Duran • The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2022)

Detecting building façade elements is a crucial problem in computer vision for image interpretation. In Building Information Modeling (BIM) studies, the detection of building façade elements has an important role. BIM is a tool that allows ...

DOAJ Open Access (DOAJ) DOI: 10.5194/isprs-archives-XLIII-B4-2022-315-2022

Scale Accuracy Evaluation of Image-Based 3D Reconstruction Strategies Using Laser Photogrammetry

Klemen Istenič, Nuno Gracias, Aurélien Arnaubec, Javier Escartín et al. • Remote Sensing (2019)

Rapid developments in the field of underwater photogrammetry have given scientists the ability to produce accurate 3-dimensional (3D) models which are now increasingly used in the representation and study of local areas of interest. This pa...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs11182093

Computer Vision and Pattern Recognition 2020

Zeynep Akata, Andreas Geiger, Torsten Sattler • International Journal of Computer Vision (2021)

This special issue covers a wide range of topics from the area of Computer Vision, Pattern Recognition, and Machine Learning.This breadth of scope is reflected by the papers included in this special issue, which touch topics including geome...

OPENALEX cc-by DOI: https://doi.org/10.1007/s11263-021-01522-3

Rethinking the Inception Architecture for Computer Vision

Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jonathon Shlens et al. • arXiv (Cornell University) (2015)

Convolutional networks are at the core of most state-of-the-art computer vision solutions for a wide variety of tasks. Since 2014 very deep convolutional networks started to become mainstream, yielding substantial gains in various benchmark...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1512.00567

OmniVO: Toward Robust Omni Directional Visual Odometry With Multicamera Collaboration for Challenging Conditions

Zeeshan Javed, Gon-Woo Kim • IEEE Access (2022)

With the recent developments in computer vision, vision-based odometry plays an increasingly important role in the field of autonomous systems. However, using traditional visual odometry or simultaneous localization and mapping (vSLAM) only...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2022.3204870