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Deep learning-based phenotyping of lettuce diseases using Efficient-FBM-FRMNet for precision agriculture.

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第一作者： Parul,Nasra

第一单位： Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, Punjab, India.

作者： Parul,Nasra ^[1] ; Sheifali,Gupta ^[1] ; Mudassir,Khan ^[2] ; Jaibir,Singh ^[3] ; Bayan,Alabdullah ^[4] ; Abrar,Almjally ^[5] ; Ruby,Pant ^[6] ; Nitin,Kumar ^[7] ; Salil,Bharany ^[1]

作者单位： Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, Punjab, India. ^[1] Department of Computer Science, College of Computer Science, Applied College Tanumah, King Khalid University, Abha, Saudi Arabia.;Jadara University Research Center, Jadara University, Irbid, Jordan. ^[2] School of Computer Science & Engineering, Galgotias University, Greater Noida, Uttar Pradesh, India. ^[3] Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. ^[4] College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia. ^[5] Department of Mechanical Engineering, Uttaranchal University, Dehradun, Uttarakhand, India. ^[6] Department of Mechanical Engineering, Graphic Era (Deemed to be University), Clement Town, Dehradun, India.;University Center for Research and Development, Chandigarh University, Mohali, Punjab, India. ^[7]

关键词 deep learning dilated convolutions efficientNetB4 feature bottleneck module (FBM)feature refinement module (FRM)lettuce disease detection

DOI 10.3389/fpls.2025.1704647

PMID 41393894

发布时间 2025-12-17

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