Zobrazeno 1 - 10
of 141
pro vyhledávání: '"leaf disease classification"'
Autor:
Yuxin Xia, Wenxia Yuan, Shihao Zhang, Qiaomei Wang, Xiaohui Liu, Houqiao Wang, Yamin Wu, Chunhua Yang, Jiayi Xu, Lei Li, Junjie He, Zhiyong Cao, Zejun Wang, Zihua Zhao, Baijuan Wang
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract To address the issues of low accuracy and slow response speed in tea disease classification and identification, an improved YOLOv7 lightweight model was proposed in this study. The lightweight MobileNeXt was used as the backbone network to r
Externí odkaz:
https://doaj.org/article/967a195f14fc4a54a83cbbc8dd11f0d5
Autor:
Khaoula Taji, Ali Sohail, Tariq Shahzad, Bilal Shoaib Khan, Muhammad Adnan Khan, Khmaies Ouahada
Publikováno v:
IEEE Access, Vol 12, Pp 61886-61906 (2024)
A stable and sustainable food supply chain is only possible with effective agriculture management. The application of technology in agriculture has recently produced encouraging outcomes in terms of improving agricultural yield and quality. Early det
Externí odkaz:
https://doaj.org/article/5e128800673b496dafa23eb793fa01c4
Autor:
Mehedi Hasan Bijoy, Nirob Hasan, Mithun Biswas, Suvodeep Mazumdar, Andrea Jimenez, Faisal Ahmed, Mirza Rasheduzzaman, Sifat Momen
Publikováno v:
IEEE Access, Vol 12, Pp 34174-34191 (2024)
Rice is one of the foremost food grains that dispenses sustenance to about half of the world’s population. It is cultivated all over the world. The leaf disease detection of this crop is one of the chronic agricultural obstacles that farmers and pl
Externí odkaz:
https://doaj.org/article/d75f01af63dc41f794b8a6e84982a86e
Autor:
Shaik Salma Asiya Begum, Hussain Syed
Publikováno v:
IEEE Access, Vol 12, Pp 32493-32506 (2024)
Nowadays, the demand for pepper keeps on increasing with the increase in human population. Accurate diagnosis, flawless identification, and early detection of the lesions will improve the income of farmers. At present, deep learning (DL) based techni
Externí odkaz:
https://doaj.org/article/b3b063a6df434aadadbba3c586f662d6
Publikováno v:
Applied Sciences, Vol 14, Iss 17, p 7472 (2024)
Recently, convolutional neural networks (CNNs) and self-attention mechanisms have been widely applied in plant disease identification tasks, yielding significant successes. Currently, the majority of research models for tomato leaf disease recognitio
Externí odkaz:
https://doaj.org/article/ef9f9605e0cb42e58529b44f6b7eb54c
Publikováno v:
Big Data and Cognitive Computing, Vol 8, Iss 6, p 52 (2024)
Due to the projected increase in food production by 70% in 2050, crops should be additionally protected from diseases and pests to ensure a sufficient food supply. Transfer deep learning approaches provide a more efficient solution than traditional m
Externí odkaz:
https://doaj.org/article/33cc45a698e7441fa2ebbac092d2c68f
Publikováno v:
IEEE Access, Vol 11, Pp 62281-62291 (2023)
Coffee leaf diseases can significantly impact the productivity and quality of the crops. Accurate and timely identification of these diseases is crucial for effective management and control. This paper proposes a hybrid feature fusion approach for id
Externí odkaz:
https://doaj.org/article/2678871784a8418c874b3e95a5350e26
Akademický článek
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Akademický článek
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K zobrazení výsledku je třeba se přihlásit.
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Autor:
Ihtiram Raza Khan, M. Siva Sangari, Piyush Kumar Shukla, Aliya Aleryani, Omar Alqahtani, Areej Alasiry, M. Turki-Hadj Alouane
Publikováno v:
Biomimetics, Vol 8, Iss 5, p 438 (2023)
In recent years, disease attacks have posed continuous threats to agriculture and caused substantial losses in the economy. Thus, early detection and classification could minimize the spread of disease and help to improve yield. Meanwhile, deep learn
Externí odkaz:
https://doaj.org/article/ee2f8d9c18824241937a4685272b9924