Forecasting vegetation indices from spatio-temporal remotely sensed data using deep learning-based approaches: A systematic literature review

A Ferchichi, AB Abbes, V Barra, IR Farah - Ecological Informatics, 2022‏ - Elsevier
Over the last few years, Deep learning (DL) approaches have been shown to outperform
state-of-the-art machine learning (ML) techniques in many applications such as vegetation …

Explainability in graph neural networks: A taxonomic survey

H Yuan, H Yu, S Gui, S Ji - IEEE transactions on pattern …, 2022‏ - ieeexplore.ieee.org
Deep learning methods are achieving ever-increasing performance on many artificial
intelligence tasks. A major limitation of deep models is that they are not amenable to …

Contextual Target-Specific Stance Detection on Twitter: Dataset and Method

Y Li, D Wen, H He, J Guo, X Ning… - 2023 IEEE International …, 2023‏ - ieeexplore.ieee.org
To understand different aspects of online human behaviors, eg, the public stances toward
various social and political issues, contextual target-specific stance detection has become …

3D Convolutional Neural Network with Dimension Reduction and Metric Learning for Crop Yield Prediction Based on Remote Sensing Data

N Wang, Z Ma, P Huo, X Liu, Z He, K Lu - Applied Sciences, 2023‏ - mdpi.com
Crop yield prediction is essential for tasks like determining the optimal profile of crops to be
planted, allocating government resources, effectively planning and preparing for aid …

Development of Convolutional Neural Network Model for Crop Yield Prediction

S Ghildiyal, A Deogaonkar, NS Bhandari… - … on Intelligent Cyber …, 2024‏ - ieeexplore.ieee.org
Smart cultivation may help improve water management and food production, minimizing the
adverse consequences of increased human growth. Crop yield prediction is primarily …

Predicting Crop Yield Using 3D Convolutional Neural Network with Dimension Reduction and Metric Learning

N Wang, Z Ma, P Huo, X Liu - 2023 IEEE 6th International …, 2023‏ - ieeexplore.ieee.org
Crop yield prediction using remote sensing data during the growing season is helpful to farm
planning and management, which has received more and more attention. Information …