Results 21 to 30 of about 338 (99)

The Evolution of Impression Management Research in Social Media: A Bibliometric Perspective

Corporate Social Responsibility and Environmental Management, Volume 33, Issue 3, Page 4070-4087, May 2026.
ABSTRACT The purpose of the present study is to investigate impression management (IM) usage by companies in the context of social media communication and emerging technologies through a comprehensive mapping of the scientific literature. In this matter, a bibliometric analysis has been conducted, extracting a sample of 262 peer‐reviewed journal ...
Antonio Iazzi, Amedeo Maizza, Simona Lamusta, Simone Pizzi   +3 more
wiley   +1 more source

Mitochondrial morphology in human fibroblasts and induced pluripotent stem cells in Leigh syndrome: A comparative analysis

Physiological Reports, Volume 14, Issue 9, May 2026.
Abstract Mitochondria are dynamic organelles that regulate several vital cellular functions in both health and disease. Accurately quantifying different mitochondrial shapes using simple, affordable techniques remains challenging. We have previously developed a Mitochondrial Cellular Phenotype (MitoCellPhe) tool to quantify 24 different mitochondrial ...
Fibi Meshrkey, Ajibola B. Bakare, Raj R. Rao, Shilpa Iyer   +3 more
wiley   +1 more source

Method for quickly building road network model of open-pit mine based on grid refinement

Meitan xuebao
Constructing the road network in open-pit mining areas is a crucial step for intelligent scheduling and autonomous driving of trucks in these regions. However, given the intricate road conditions, extensive GPS trajectory data from mining vehicles, and ...
Qinghua GU, Fengyuan HU, Qian WANG, Xiaobo CHAI, Dan WANG, Xinxin JING   +5 more
doaj   +1 more source

From Satellite to Shapefiles: ZymbaNet For Memory‐Efficient Automated Road Mapping

Transactions in GIS, Volume 30, Issue 2, April 2026.
ABSTRACT Road network extraction from very‐high‐resolution (VHR) satellite imagery is a fundamental task in geospatial applications such as urban planning, navigation, and geographic information systems (GIS). Despite significant progress achieved by convolutional and attention‐based architectures, existing methods still face two critical challenges ...
Mohamed El Mehdi Imam, Lila Meddeber, Soufyane Bouchelaghem, Tarik Zouagui, Marco BalsI   +4 more
wiley   +1 more source

Automated quantification of fine root production from minirhizotron image time series

Methods in Ecology and Evolution, Volume 17, Issue 3, Page 758-767, March 2026.
Abstract Plant root growth accounts for a major part of the net primary production in grassland and forest ecosystems and influences the global carbon and nutrient cycles. Measuring the production of roots is inherently difficult, prone to inconsistencies and time‐consuming. Notably, there are currently no methods yet to automate this task.
Alexander Gillert, Patrick Möhl, Bo Peters, Lionel Safar, Julia Bebout, Stuart Schwab, Erika Hiltbrunner, Jürgen Kreyling, Tara Javidi, Elsa Cleland   +9 more
wiley   +1 more source

Grapevine Branch Recognition and Pruning Point Localization Technology Based on Image Processing

Applied Sciences
The identification of branches and bud points is the key to intelligent pruning of dormant grapevine branches and precise positioning of the pruning point on the branch is an important prerequisite for robotic arm pruning.
Zhangnan Chen, Yaxiong Wang, Siyuan Tong, Chongchong Chen, Feng Kang   +4 more
doaj   +1 more source

AI and Measurement Concerns: Dealing with Imbalanced Data in Autoscoring

Journal of Educational Measurement, Volume 63, Issue 1, Spring 2026.
Abstract Unbiasedness for proficiency estimates is important for autoscoring engines since the outcome might be used for future learning or placement. Imbalanced training data may lead to certain biases and lower the prediction accuracy for classification algorithms.
Yunting Liu, Yijun Xiang, Xutao Feng, Mark Wilson   +3 more
wiley   +1 more source

Transparency and Trust in Simple Algorithmic Hiring Procedures

International Journal of Selection and Assessment, Volume 34, Issue 1, February 2026.
ABSTRACT It is well established that combining information via a simple algorithm (mechanical combination) results in better hiring decisions than a holistic combination. Nevertheless, mechanical combination is perceived negatively and rarely used in practice. Transparency is an often‐mentioned determinant of algorithmic trust in the AI‐literature, but
A. Susan M. Niessen, Marvin Neumann
wiley   +1 more source

Vector‐Based and Machine Learning Approaches for Pore Network Parameters Analysis

Geophysical Prospecting, Volume 74, Issue 1, January 2026.
ABSTRACT Accurate characterization of pore structures in carbonate rocks is critical for evaluating fluid flow and storage capacity in subsurface reservoirs, a key concern in geophysical exploration and reservoir engineering. This study proposes a hybrid digital rock physics workflow that integrates deep learning–based segmentation, vectorial geometric
José Frank V. Gonçalves, José J. S. de Figueiredo, João Rafael B. S. Da Silveira, Pedro T. P. Aum, Daniel N. N. Da Silva   +4 more
wiley   +1 more source

Machine Vision–Based Defect Detection and Quantitative Assessment for Pavement Maintenance

Structural Control and Health Monitoring, Volume 2026, Issue 1, 2026.
An efficient detection and quantification of pavement defects is a significant challenge for intelligent road maintenance; nevertheless, current methodologies exhibit poor accuracy, inadequate lightweight characteristics, and substantial 2D quantification errors. This paper proposes a collection of efficient and lightweight methods.
Chenlang Zhou, Yiqiang Sun, Shijie Zhou, Xianjie Deng, Puzhong Wang, Fabio Casciati   +5 more
wiley   +1 more source