Search Results - "Image recognition"

Deep Learning for Image-Recognition-Based Cassava Disease Detection by CGIAR Platform for Big Data in Agriculture

“…Results show that image recognition is an easily deployable strategy for disease detection.…”
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WP1-OP3: Toolbox for molecular detection and image recognition, characterization, monitoring and surveillance of a broad range of P&D by Juanillas, Venice Margarette, Pinili, Dale, Schepler-Luu, Van

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Deep learning for image-based cassava disease detection by Ramcharan, A., Baranowski, K., McCloskey, P., Ahmed, B., Legg, James P., Hughes, D.P.

“…Novel methods of cassava disease detection are needed to support improved control which will prevent this crisis. Image recognition offers both a cost effective and scalable technology for disease detection. …”
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Tropical forages identification tool: A new companion for tropical forages selection tool by Cardoso, Juan Andrés

“…There has been a recent explosion in the development of image recognition technology and its application to automated plant identification, so it is timely to consider its potential for the identification of tropical forages in the field. …”
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Innovative digital technologies to monitor and control pest and disease threats in Root, Tuber, and Banana (RT&B) cropping systems: progress and prospects by Kreuze, Jan F., Adewopo, Julius, Selvaraj, Michael, Mwanzia, Leroy, Kumar, P. Lava, Cuéllar, Wilmer Jose, Legg, James P., Hughes, D.P., Blomme, Guy

“…We also present ideas on the use of image recognition from smartphones or unmanned aerial vehicles (UAVs) for pest and disease monitoring and data processing for modeling, predictions, and forecasting regarding climate change. …”
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Exploring an artificial intelligence–based, gamified phone app prototype to track and improve food choices of adolescent girls in Vietnam: Acceptability, usability, and likeability... by Braga, Bianca C., Nguyen, Phuong Hong, Aberman, Noora-Lisa, Doyle, Frank, Folson, Gloria, Hoang, Nga Thu, Huynh, Phuong, Koch, Bastien, McCloskey, Peter, Tran, Lan, Hughes, David, Gelli, Aulo

“…Objective: This study aimed to examine the acceptability, usability, and likability of a mobile phone app prototype developed to collect dietary data using artificial intelligence–based image recognition of foods, provide feedback, and motivate users to make healthier food choices. …”
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Measuring adherence, acceptability and likability of an artificial-intelligence-based, gamified phone application to improve the quality of dietary choices of adolescents in Ghana... by Braga, Bianca C., Arrieta, Alejandra, Bannerman, Boateng, Doyle, Frank, Koch, Bastien, Nguyen, Phuong Hong, Gelli, Aulo

“…In each country, 36 adolescents (12–18 years) will be randomly allocated into two groups: The intervention group with the full version of FRANI and the control group with the functionality limited to image recognition and dietary assessment. Participants in both groups will have their food choices tracked for four weeks. …”
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MusaDeepMosaic: Development of a machine learning genomic mosaic classifier tool. by Vicens, Romain, Cenci, Alberto, Guillaume, Martin, Sardos, Julie, Rouard, Mathieu, Breton, Catherine

“…The ResNet-50 model, a 50-layer deep convolutional neural network introduced in 2015 for image recognition, was utilized in this study. Optimized for accurate performance and fast processing times, ResNet-50 will be integrated into an automated system capable of characterizing newly genotyped individuals, analyzing the new genetic data, and automatically assigning individuals to the appropriate diversity groups. …”
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