Identifying barley varieties by computer vision
https://doi.org/10.1016/j.compag.2014.09.016
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https://doi.org/10.1016/j.compag.2014.09.016
Background: Artificial Intelligence (AI) has emerged as a transformative tool in in vitro fertilization (IVF) as it has done in other sectors. In IVF, AI offers advancements in embryo selection, treatment personalization, and outcome predic...
10.3390/biology15010042
10.1038/s44298-026-00193-6
PMC: PMC13728169
Educational robotics has gained a lot of attention in the past few years in K-12 education. Prior studies have shown enough shreds of evidence and highlight the benefits of educational robotics as being effective in providing impactful lear...
https://doi.org/10.3390/electronics10060730
The rapid advancement of Artificial Intelligence (AI), wearable computing, and Internet of Things (IoT) technologies has significantly transformed digital interactions across various sectors. However, the adoption of smart wearable technolo...
10.5281/zenodo.21981139
This study presents a comprehensive study of a novel Contact-Based Pose Estimation Method (CBPEM) for enhancing precision in robotic assembly processes within digital twin frameworks. Conventional pose detection methods, such as laser and c...
10.1051/mfreview/2025004
10.1007/s00066-026-02558-5
PMC: PMC13731520
Pedestrian detection is one of the most widely applied tasks in industrial computer vision. It encapsulates three core challenges of object detection: detecting small objects, handling heavy occlusion, and balancing speed and accuracy for d...
10.5194/ms-16-877-2025
Abstract We present a Wilson–Cowan reservoir computer (WC–RC) that treats a retinotopic excitatory–inhibitory neural field as a structured reservoir. Travelling waves and bounded oscillations provide an interpretable spatiotemporal basis, w...
10.1038/s41598-026-49359-5
Representing videos by densely extracted local space–time features has recently become a popular approach for analysing actions. In this study, the authors tackle the problem of categorising human actions by devising bag of words (BoWs) mod...
10.1049/iet-cvi.2014.0018
Sustainable food production increasingly relies on intelligent automation technologies that optimize resource usage while maintaining crop health. This study presents a deep learning-driven computer vision and web based monitoring system de...
10.15832/ankutbd.1817471
Surveillance videos are crucial for crime prevention and public safety, yet the challenge of defining abnormal events hinders their effectiveness, limiting the applicability of supervised methods. This paper introduces an unsupervised end-t...
10.1109/ACCESS.2024.3435144
10.1186/s12896-026-01210-5
PMC: PMC13732988
Translating satellite imagery into maps requires intensive effort and time, especially leading to inaccurate maps of the affected regions during disaster and conflict. The combination of availability of recent datasets and advances in compu...
10.3389/frai.2020.534696
The methods of deep learning have lately demonstrated outstanding outcomes of robotic objects such as imagination, localization and striping. Its exceptional abilities in order to learn idealizations from complicated data gathered in the re...
10.1051/bioconf/20249700008
10.3389/fnbot.2026.1934032
PMC: PMC13735105
10.3389/fbioe.2026.1952925
PMC: PMC13736717
10.1016/j.jgeb.2026.100840
PMC: PMC13737746
Abstract In this paper, we investigate the spatiotemporal patterns of a freshwater tussock sedge model with discrete time and space variables. We first analyze the kinetic system and show the parametric conditions for flip and Neimark–Sacke...
10.1186/s13662-021-03557-9
Monitoring and understanding fish behavior is crucial for achieving precision in everyday husbandry practices (i.e. for optimizing farm performance), and for improving fish welfare in aquaculture. Various intelligent monitoring and control ...
10.3389/fanim.2021.754520