Search Results - "machine"

A robust model based on root morphological and anatomical features to distinguish high and low methane emission rice varieties through machine learning approaches by Roy, Ripon Kumar, Hosseiniyan Khatibi, Seyed Mahdi, Kim, Sung-Ryul, Trijatmiko, Kurniawan Rudi, Diaz, Maria Genaleen Q., Ocampo, Eureka Teresa M., Hernandez, Jose E., Pirmoradi, Saeed, Henry, Amelia, Kohli, Ajay

Subjects: “…machine learning…”
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Detection of Alternaria padwickii (Ganguly) M.B. Ellis in Rice Seeds Using Hyperspectral Imaging to Enhance Seed Health Assessment in Germplasm Exchange by Cortez, Camille Rae, Castellion, Martina, Catausan, Sheryl, Gentallan, Renerio Jr., Calayugan, Mark Ian, Mercado, Ma. Fatima O., Hay, Fiona R.

Subjects: “…machine learning…”
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Online fitted policy iteration based on extreme learning machines by Escandell-Montero, Pablo, Lorente, Delia, Martínez-Martínez, José M., Soria-Olivas, Emilio, Vila-Francés, Joan, Martín-Guerrero, José D.

Subjects: “…Extreme learning machine…”
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Applying Swedish programmes projecting forest development to Polish forestry conditions : a study made on data from Gostynin forest district in Poland by Skreta, Magdalena

Subjects: “…Forest Time Machine…”

About identification of features that affect the estimation of citrus harvest by Brenes Pérez, Cristian F., y 5 autores más

Subjects: “…machine learning…”
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Digital soil mapping of metals and metalloids in croplands using multiple geospatial data and machine learning, implemented in GEE, for the Peruvian Mantaro Valley by Pizarro Carcausto, Samuel, Vera Vilchez, Jesús Emilio, Huamani, Joseph, Cruz, Juancarlos, Lastra Paucar, Sphyros Roomel, Solórzano Acosta, Richard Andi, Verástegui Martínez, Patricia

Subjects: “…Machine learning…”
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Estimation of forage biomass in oat (Avena sativa) using agronomic variables through UAV multispectral imaging by Urquizo Barrera, Julio Cesar, Ccopi Trucios, Dennis, Ortega Quispe, Kevin, Castañeda Tinco, Italo, Patricio Rosales, Solanch, Passuni Huayta, Jorge, Figueroa Venegas, Deyanira, Enriquez Pinedo, Lucia, Ore Aquino, Zoila, Pizarro Carcausto, Samuel

Subjects: “…Machine learning…”
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Ecological niche modeling approach for assessing potential for expansion of irrigated rice under alternate wetting and drying method by CGIAR Research Program on Climate Change, Agriculture and Food Security

Subjects: “…machine learning…”
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Pollination supply models from a local to global scale by Giménez-García, Angel, Allen-Perkins, Alfonso, Bartomeus, Ignasi, Balbi, Stefano, Knapp, Jessica L., Hevia, Violeta, Woodcock, Ben Alex, Smagghe, Guy, Miñarro, Marcos, Eeraerts, Maxime, Colville, Jonathan F., Hipólito, Juliana, Cavigliasso, Pablo, Nates-Parra, Guiomar, Herrera, José M., Cusser, Sarah, Simmons, Benno I., Wolters, Volkmar, Jha, Shalene, Freitas, Breno M., Horgan, Finbarr G., Artz, Derek R., Sidhu, Sheena, Otieno, Mark, Boreux, Virginie, Biddinger, David J., Klein, Alexandra-Maria, Joshi, Neelendra K., Stewart, Rebecca I.A., Albrecht, Matthias, Nicholson, Charlie C., O’Reilly, Alison D., Crowder, David William, Burns, Katherine L.W., Nabaes Jodar, Diego Nicolás, Garibaldi, Lucas Alejandro, Sutter, Louis, Dupont, Yoko L., Dalsgaard, Bo, da Encarnação Coutinho, Jeferson Gabriel, Lázaro, Amparo, Andersson, Georg K.S., Raine, Nigel E., Krishnan, Smitha, Dainese, Matteo, van der Wer, Wopke, Smith, Henrik G., Magrach, Ainhoa

Subjects: “…pollination supply models, ecological intensification, global, pollinators, machine learning…”
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Predicting turbidity dynamics in small reservoirs in Central Kenya using remote sensing and machine learning by Steinbach, S., Bartels, A., Rienow, A., Kuria, B. T., Zwart, Sander J., Nelson, A.

Subjects: “…machine learning…”
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Robustness of the RGB image-based estimation for rice above-ground biomass by utilizing the dataset collected across multiple locations by Nakajima, Kota, Saito, Kazuki, Tsujimoto, Yasuhiro, Takai, Toshiyuki, Mochizuki, Atsushi, Yamaguchi, Tomoaki, Ibrahim, Ali, Mairoua, Salifou Goube, Andrianary, Bruce Haja, Katsura, Keisuke, Tanaka, Yu

Subjects: “…machine learning…”
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Technical report: Next-Generation decision support tool for data-driven fertilizer recommendations to enhance maize performance in Ethiopia by Mesfin, Tewodros, Abera, Wuletawu, Ebrahim, Mohammed, Tilaye, Amsalu, Tibebe, Degefie, Tamene, Lulseged, Adimassu, Zenebe, Liben, Feyera, Bekere, Jemal, Nazib, Nibras

Subjects: “…machine learning…”
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Detección de outliers en muestras de entrenamiento generadas mediante interpretación visual by Banchero, Santiago, Veron, Santiago Ramón, Petek, Mariana, Sarrailhe, Sofia, De Abelleyra, Diego

Subjects: “…Machine Learning…”
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Predicting the fundamental fluxes of an eddy-covariance station using machine learning methods by García-Rodríguez, David, Catret, Pablo, Iglesias, Domingo J., Martínez, Juan J., López, Ernesto, García, Antonio

Subjects: “…machine learning…”
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Naturlig föryngring efter markberedning med harv eller Bracke Planter i Småland by Sjögren, Vidar

Subjects: “…planting machine…”

Predicting infectious diseases: a bibliometric review on Africa by Phoobane, P., Masinde, M., Mabhaudhi, Tafadzwanashe

Subjects: “…machine learning…”
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Banana mapping in heterogenous smallholder farming systems using high-resolution remote sensing imagery and machine learning models with implications for banana bunchy top disease... by Alabi, T.R., Adewopo, Julius, Duke, O.P., Kumar, P. Lava

Subjects: “…machine learning…”
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Machine learning based groundwater prediction in a data-scarce basin of Ghana by Siabi, E. K., Dile, Y. T., Kabo-Bah, A. T., Amo-Boateng, M., Anornu, G. K., Akpoti, Komlavi, Vuu, C., Donkor, P., Mensah, S. K., Incoom, A. B. M., Opoku, E. K., Atta-Darkwa, T.

Subjects: “…machine learning…”
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Multiyear Maize management dataset collected in Chiapas, Mexico by Trevisan, Rodrigo G., Martin, Nicolas F., Fonteyne, Simon, Verhulst, Nele, Dorado Betancourt, Hugo Andres, Jiménez, Daniel, Gardeazábal Monsalve, Andrea

Subjects: “…machine learning…”
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Near real-time monitoring of cassava cultivation area by Phan, Trong Van, Reymondin, Louis, Vantalon, Thibaud, Delaquis, Erik, Nguyen, Thuy Thanh, Mienmany, Bandit

Subjects: “…machine learning…”
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