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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

Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead

Maurizio Capra, Beatrice Bussolino, Alberto Marchisio, Guido Masera et al. • IEEE Access (2020)

Currently, Machine Learning (ML) is becoming ubiquitous in everyday life. Deep Learning (DL) is already present in many applications ranging from computer vision for medicine to autonomous driving of modern cars as well as other sectors in ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2020.3039858

Automated detection of bicycle helmets using deep learning

Felix Wilhelm Siebert, Christoffer Riis, Kira Hyldekær Janstrup, Hanhe Lin et al. • Journal of Cycling and Micromobility Research (2024)

Bicycle helmets are a main measure for injury prevention in case of a crash and are a central variable in transport safety studies. Despite this, helmet use data is only collected sporadically, as the observation of helmet use in traffic by...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jcmr.2024.100013

Deep learning based identification and tracking of railway bogie parts

Muhammad Zakir Shaikh, Zeeshan Ahmed, Enrique Nava Baro, Samreen Hussain et al. • Alexandria Engineering Journal (2024)

The Train Rolling-Stock Examination (TRSE) is a safety examination process that physically examines the bogie parts of a moving train, typically at speeds over 30 km/h. Currently, this inspection process is done manually by railway personne...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.aej.2024.07.064

Vision-Based Trajectory Generation and Kinematic Modeling for Human-like Grasp Reproduction in a Robotic Prosthetic Hand

Renzo Fernández, Néstor Zamora, Victor Coloma, Nino Vega et al. • Technologies (2026)

The use of prosthetic devices can significantly improve the quality of life of individuals with limb amputations. However, existing prosthetic hands face multiple engineering and manufacturing challenges, making them economically inaccessib...

DOAJ Open Access (DOAJ) DOI: 10.3390/technologies14060334

Applied research note: Predicting carcass portion weights for purebred turkey (Meleagris gallopavo) lines using a 2D imaging system

Shai Barbut, Emily M. Leishman, Ryley J. Vanderhout, Benjamin J. Wood et al. • Journal of Applied Poultry Research (2025)

Summary: Improving carcass portion yields (e.g., breast meat) is a major goal of modern turkey breeding and traditionally requires manual collection of portion weights. This can be a labor-intensive process considering the large amount of d...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.japr.2024.100506

Tamarind health assessment dataset: Images of shelled, unshelled, and mixed tamarind podsMendeley Data

Amol Bhosle, Deepali Godse, Sandip Thite, Kailas Patil et al. • Data in Brief (2025)

This data paper provides image dataset that includes 8432 high-quality images of Tamarindus indica [1] (tamarind), categorized into six types: Shelled Healthy Single, Shelled Healthy Multiple, Unshelled Healthy Single, Unshelled Healthy Mul...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.dib.2025.111917

A critical review on computer vision and artificial intelligence in food industry

Vijay Kakani, Van Huan Nguyen, Basivi Praveen Kumar, Hakil Kim et al. • Journal of Agriculture and Food Research (2020)

Emerging technologies such as computer vision and Artificial Intelligence (AI) are estimated to leverage the accessibility of big data for active training and yielding operational real time smart machines and predictable models. This phenom...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.jafr.2020.100033

Rethinking the Inception Architecture for Computer Vision

Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens et al. • IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings (2016)

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 DOI: https://doi.org/10.1109/cvpr.2016.308

A lightweight fully convolutional neural network for efficient and accurate tunnel crack detection

Hao Huang, G.T.S. Ho, V. Tang, E.W.H. Chow et al. • Journal of Advanced Research (2026)

Introduction: Crack damage is a significant issue in tunnel environments, requiring efficient and reliable detection to ensure structural integrity. Many existing solutions are computationally expensive, making them unsuitable for the tight...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jare.2025.11.052

Impact of Water Depth on Subway Emergency Evacuation in Flood Scenarios

ZHU Wenhao, ZHU Haiyan, LIU Zhigang, SHEN Yuxin et al. • Chengshi guidao jiaotong yanjiu (2025)

[Objective] Evacuation bottlenecks for subway stations in flood scenarios are investigated to enhance subway station personnel evacuation efficiency under water inundation and backflow conditions, and provide insights for developing subway ...

DOAJ Open Access (DOAJ) DOI: 10.16037/j.1007-869x.20231053

A SMARTPHONE-BASED 3D PIPELINE FOR THE CREATIVE INDUSTRY – THE REPLICATE EU PROJECT

E. Nocerino, F. Lago, D. Morabito, F. Remondino et al. • The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2017)

During the last two decades we have witnessed great improvements in ICT hardware and software technologies. Three-dimensional content is starting to become commonplace now in many applications. Although for many years 3D technologies have b...

DOAJ Open Access (DOAJ) DOI: 10.5194/isprs-archives-XLII-2-W3-535-2017