Crop and Weed Classification Using Deep Learning
Main Article Content
Abstract
Information technology is prominent in precision agriculture and also support the agronomist in agro business. Usually, weeds grow along with the crops and reduces the yield of that crop. Herbicides are used to remove the weeds. Without the identification of the type of the weed, the herbicide may damage the crop too. It is necessary to identify and classify the weeds from the farms in order to control them. Deep learning-based computer vision technique, Conv Net or CNN is used to analyse images. This paper proposed a CNN based deep learning model to identify the weeds and crops from the farm field. Based on the predictions the type of herbicide will be suggested to the farmers.
Article Details
Issue
Section
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.