A temporal fusion transformer deep learning model for long-term streamflow forecasting: a case study in the funil reservoir, Southeast Brazil

G Fayer, L Lima, F Miranda… - Knowledge …, 2023 - … journals.publicknowledgeproject.org
Water reservoirs play a critical role in water resource management systems, serving various
purposes such as water supply, hydropower generation, and flood control. Accurate long …

Develo** a comprehensive evaluation model of variety adaptability based on machine learning method

Y Han, K Wang, Q Zhang, F Yang, S Pan, Z Liu… - Field Crops …, 2024 - Elsevier
Context or problem A comprehensive evaluation of the adaptability of maize varieties is very
important to accurately promote new varieties and reduce the risk of using them. However …

A Novel Framework using deep learning techniques for Ragi Price Prediction in Karnataka

K Meena, B Chaitra - IEEE Access, 2024 - ieeexplore.ieee.org
Indian agriculture is diverse, employing a significant portion of the country's population. In
southern states of India, Rice and Ragi are the main crops. Ragi cultivation provides …

Maize hybrids performance evaluation with Data Fusion by Matrix Factorization algorithm

M Brkić, S Hačko, M Radovanović… - Applied Artificial …, 2024 - Taylor & Francis
Crop breeders often face challenges due to limited data availability when making crucial
decisions, such as selecting top-performing varieties/hybrids for further experiments …

Time series forecasting of wheat crop productivity in egypt using deep learning techniques

A Mahmoud, A Mohammed, MM abdel wahab… - International Journal of …, 2024 - Springer
Egypt's agricultural sector plays a critical role in the country's economy, with wheat
cultivation being vital for ensuring food security. However, the challenges faced by wheat …

Efficient representation learning of satellite image time series and their fusion for spatiotemporal applications

P Goyal, A Kaur, A Ram, N Goyal - … of the AAAI Conference on Artificial …, 2024 - ojs.aaai.org
Satellite data bolstered by their increasing accessibility is leading to many endeavors of
automated monitoring of the earth's surface for various applications. Such applications …

An innovative smart agriculture system utilizing a deep neural network and embedded system to enhance crop yield

AG Chandar, K Sivasankari, SL Lakshmi… - Multidisciplinary …, 2024 - malquepub.com
Wheat crop classification and prediction are important tasks for the optimization of crop yield
and resource utilization. In this study, we propose an Artificial Neural Network (ANN) model …

Utilizing MODIS Fire Mask for Predicting Forest Fires Using Landsat-9/8 and Meteorological Data

Y Gupta, N Goyal, VJ Varghese… - 2023 IEEE 10th …, 2023 - ieeexplore.ieee.org
Recent years have seen some of the largest forest fires ever, including the 2020 California
megafires and the Australian bushfires, causing billions of dollars in property damage and …

Predicting wheat yield in agricultural industry using deep learning techniques: a review

P Bari, L Ragha - Nigerian Journal of Technology, 2024 - ajol.info
In the post-pandemic future, technology in the agriculture industry can improve food
sustainability while moderating the use of resources of nature in a variety of conditions …

Spatial-channel transformer network based on mask-RCNN for efficient mushroom instance segmentation

J Wang, W Song, W Zheng, Q Feng, M Wang… - International Journal of …, 2024 - ijabe.org
Edible mushrooms are rich in nutrients; however, harvesting mainly relies on manual labor.
Coarse localization of each mushroom is necessary to enable a robotic arm to accurately …