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A Deep Learning-Based System (Microscan) for the Identification of Pollen Development Stages and Its Application to Obtaining Doubled Haploid Lines in Eggplant.
García-Fortea Edgar, García-Pérez Ana, Gimeno-Páez Esther, Sánchez-Gimeno Alfredo, Vilanova Santiago, Prohens Jaime, Pastor-Calle David
RetinaNet, Solanum melongena, androgenesis, anther culture, microspores
Early diagnosis of COVID-19-affected patients based on X-ray and computed tomography images using deep learning algorithm.
In Soft computing
Dansana Debabrata, Kumar Raghvendra, Bhattacharjee Aishik, Hemanth D Jude, Gupta Deepak, Khanna Ashish, Castillo Oscar
CNN, COVID-19, CT scan, Decision tree, Inception_V2, VGG-16, X-ray images
Alberto Sabater, Luis Montesano, Ana C. Murillo
Shakib Yazdani, Shervin Minaee, Rahele Kafieh, Narges Saeedizadeh, Milan Sonka
Feasibility of Training a Random Forest Model With Incomplete User-Specific Data for Devising a Control Strategy for Active Biomimetic Ankle.
In Frontiers in bioengineering and biotechnology
Dey Sharmita, Yoshida Takashi, Schilling Arndt F
human gait, intelligent biomimetics, prediction, prosthetic control, random forest
In Frontiers in medicine
Yao Ren-Qi, Jin Xin, Wang Guo-Wei, Yu Yue, Wu Guo-Sheng, Zhu Yi-Bing, Li Lin, Li Yu-Xuan, Zhao Peng-Yue, Zhu Sheng-Yu, Xia Zhao-Fan, Ren Chao, Yao Yong-Ming
coagulation, extreme gradient boosting, intensive care unit, postoperative sepsis, prediction