Resultados de búsqueda - Machine industry

Liberalise trade in machines por Ajmani, Manmeet Singh, Roy, Devesh, Takeshima, Hiroyuki

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Machine vision for precise control of weeds por Blasco, José, Benlloch, J. V., Agustí, Manuel, Moltó, Enrique

“…Image processing techniques have been traditionally used in the industry, where controlling most of the environmental variables (mainly lighting, background and speed) uses to be easy. …”
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Comparative analysis of rice grain quality and climate change impacts in temperate production zones from an Australian rice industry perspective por Fernando, Yvonne, Ovenden, Ben, Sreenivasulu, Nese, Butardo, Vito

“…Climate change poses major challenges for temperate rice production systems, with significant implications on rice grain quality, impacting the consumer markets and thus forth addressing unimpaired grain quality solutions is vital for industry profita-bility. This review synthesizes current knowledge of climate-induced quality changes in temperate-grown rice, focusing on the Australian industry as a primary case study alongside comparisons with other temperate regions. …”
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Reviving the Ganges water machine: potential and challenges to meet increasing water demand in the Ganges River Basin por Amarasinghe, Upali A., Muthuwatta, Lal P., Smakhtin, Vladimir U., Surinaidu, Lagudu, Natarajan, R., Chinnasamy, Pennan, Kakumanu, Krishna Reddy, Prathapar, Sanmugam A., Jain, S.K., Ghosh, N.C., Singh, S., Sharma, A., Kumar, S., Goel, M.K.

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Automatic inspection of satsuma slices using a machine vision system por Blasco, José, Cubero, Sergio, Alegre, Santiago, Arias, R., Alamar, María C., Juste, Florentino, Moltó, Enrique

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Development of a machine for the automatic sorting of pomegranate (Punica granatum) arils based on computer vision por Blasco, José, Cubero, Sergio, Gómez-Sanchís, Juan, Mira, P., Moltó, Enrique

“…Subsequently, the complete machine was tested in industry by working in real conditions throughout a whole pomegranate season, in which it automatically sorted more than nine tons of arils.…”
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Automated systems based on machine vision for inspecting citrus fruits from the field to postharvest - A review por Cubero, Sergio, Lee, Won Suk, Aleixos, Nuria, Albert, Francisco, Blasco, José

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Automated Systems Based on Machine Vision for Inspecting Citrus Fruits from the Field to Postharvest—a Review por Cubero, Sergio, Lee, Won Suk, Aleixos, Nuria, Albert, Francisco, Blasco, José

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A protocol for measuring disease resistance to Cassava Bacterial Blight, using machine-learning image analysis por Pardo, Juan Manuel, Jiménez Polo, Jenyfer, Rodríguez, Rafael, Leiva Sandoval, Ana Maria, Cuéllar, Wilmer Jose

“…A protocol for measuring disease resistance to Cassava Bacterial Blight, using machine-learning image analysis Cassava (Manihot esculenta Crantz), a starchy root crop, is the fourth most important source of dietary carbohydrate in developing countries and important source of industrial raw material in tropical regions especially in southeast Asia (SEA). …”
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Enhancing irrigation management: Unsupervised machine learning coupled with geophysical and multispectral data for informed decision-making in rice production por Chaali, Nesrine, Ramírez Gomez, Carlos Manuel, Jaramillo Barrios, Camilo Ignacio, Garr´e, Sarah, Barrero, Oscar, Ouazaa, Sofiane, Calderon Carvajal, John Edinson

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Kostnader vid gallring med flerträdshanterande aggregat, från skog till industri por Burström, Adam, Johansson, Kristoffer

“…Costs for each machine were then calculated and the longest profitable transport distance was determined. …”

Predicting Cattle Meat Types through Machine Learning Models Trained on Rapid Evaporative Ionization Mass Spectrometry (REIMS) Data por Reyes L., Esther A.

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High-resolution global map of smallholder and industrial closed-canopy oil palm plantations por Descals, A., Wich, S., Meijaard, E., Gaveau, D.L.A., Peedell, S., Szantoi, Z.

“…The characteristic backscatter response of closed-canopy oil palm stands in Sentinel-1 and the ability of CNN to learn spatial patterns, such as the harvest road networks, allowed the distinction between industrial and smallholder plantations globally (overall accuracy =98.52±0.20 %), outperforming the accuracy of existing regional oil palm datasets that used conventional machine-learning algorithms. …”
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Samarbete mellan lantbruksföretag por Gustafsson, Jonas, Gunnarsson, Karl-Anders

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Video based deep learning deciphers honeybee waggle dances in natural conditions por Grison, Sylvain, Siddaganga, Rajath, Hedge, Shrihari, Burridge, James, Blok, Pieter M., Krishnan, Smitha, Brockmann, Axel, Guo, Wei

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Potenciando la investigación agrícola con modelos de inteligencia artificial por Ruiz-Hurtado, Andres Felipe

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Wireless wine: estimación de rendimiento y ubicación de sensores para la predicción de heladas en los viñedos por Dujovne, Diego, Watteyne, Thomas, Mercado, Gustavo, Diedrichs, Ana, Taffernaberry, Juan Carlos, Perez Peña, Jorge Esteban

Materias: “…Machine Learning…”
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Transforming Agrifood Systems in West and Central Africa Initiative por Nshimiyimana, C.

“…Furthermore, it was found that two SMEs were struggling with how machines should be used, claiming that they did not receive a machine catalogue, and that cut-a-chip was incompatible with their production system. …”
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Predicting infectious diseases: a bibliometric review on Africa por Phoobane, P., Masinde, M., Mabhaudhi, Tafadzwanashe

“…Furthermore, weather-based prediction using meteorological factors is an emerging theme, and very few studies have used the fourth industrial revolution (4IR) technologies. Therefore, there is a need to explore 4IR predicting tools such as machine learning and consider integrated approaches that are pivotal to developing robust prediction systems for infectious diseases, especially in Africa. …”
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Pasteurizadora de leche 4.0 INTA-UBA. Transformación de un sistema industria 3.0 en uno industria 4.0. por Zetola, Mariano Eduardo

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