SCANet: Implementation of Selective Context Adaptation Network in Smart Farming Applications
In the last decade, deep learning has enjoyed its spotlight as the game-changing addition to
smart farming and precision agriculture. Such development has been predominantly …
smart farming and precision agriculture. Such development has been predominantly …
Implementing a Compression Technique on the Progressive Contextual Excitation Network for Smart Farming Applications
The utilization of computer vision in smart farming is becoming a trend in constructing an
agricultural automation scheme. Deep learning (DL) is famous for the accurate approach to …
agricultural automation scheme. Deep learning (DL) is famous for the accurate approach to …
Computer vision for smart farming and sustainable agriculture
R TOMBE - 2020 IST-Africa Conference (IST-Africa), 2020 - ieeexplore.ieee.org
Developments in satellite technology, remote sensors and drone technologies are
mushrooming. These developments yield volumes of high quality scene images that require …
mushrooming. These developments yield volumes of high quality scene images that require …
An effective automatic system deployed in agricultural Internet of Things using Multi-Context Fusion Network towards crop disease recognition in the wild
Automatic crop disease recognition in the wild is a challenging topic in modern intelligent
agriculture due to the appearance variances and cluttered background among crop …
agriculture due to the appearance variances and cluttered background among crop …
Convolutional neural network application in smart farming
The agricultural sector has a very pivotal role, furthermore very important in the global
economy country in the world. The uses of machine learning become trending, and massive …
economy country in the world. The uses of machine learning become trending, and massive …
Progressive contextual excitation for smart farming application
This paper attempts to address the issue of smart farming application, which targets
discriminating distinct cocoa bean categories. In smart farming application, one critical issue …
discriminating distinct cocoa bean categories. In smart farming application, one critical issue …
Critical Information Mining Network: Identifying Crop Diseases in Noisy Environments
Y Shao, W Yang, Z Lu, H Geng, D Chen - Symmetry, 2024 - mdpi.com
When agricultural experts explore the use of artificial intelligence technology to identify and
detect crop diseases, they mainly focus on the research of a stable environment, but ignore …
detect crop diseases, they mainly focus on the research of a stable environment, but ignore …
The power of transfer learning in agricultural applications: AgriNet
Z Al Sahili, M Awad - Frontiers in Plant Science, 2022 - frontiersin.org
Advances in deep learning and transfer learning have paved the way for various automation
classification tasks in agriculture, including plant diseases, pests, weeds, and plant species …
classification tasks in agriculture, including plant diseases, pests, weeds, and plant species …
Design of a highly efficient crop damage detection ensemble learning model using deep convolutional networks
Damages to crops happen due to natural calamities, irregular fertilization, improper
treatment, etc. Estimation of this damage is important in order to plan and execute corrective …
treatment, etc. Estimation of this damage is important in order to plan and execute corrective …
An adversarial generative network for crop classification from remote sensing timeseries images
Due to the increasing demand for the monitoring of crop conditions and food production, it is
a challenging and meaningful task to identify crops from remote sensing images. The state …
a challenging and meaningful task to identify crops from remote sensing images. The state …