Transfer learning in environmental remote sensing
Abstract Machine learning (ML) has proven to be a powerful tool for utilizing the rapidly
increasing amounts of remote sensing data for environmental monitoring. Yet ML models …
increasing amounts of remote sensing data for environmental monitoring. Yet ML models …
Smart water resource management using Artificial Intelligence—A review
SR Krishnan, MK Nallakaruppan, R Chengoden… - Sustainability, 2022 - mdpi.com
Water management is one of the crucial topics discussed in most of the international forums.
Water harvesting and recycling are the major requirements to meet the global upcoming …
Water harvesting and recycling are the major requirements to meet the global upcoming …
Evaluating the efficacy of segment anything model for delineating agriculture and urban green spaces in multiresolution aerial and spaceborne remote sensing …
Segmentation of Agricultural Remote Sensing Images (ARSIs) stands as a pivotal
component within the intelligent development path of agricultural information technology …
component within the intelligent development path of agricultural information technology …
[HTML][HTML] Statistical and deep learning models for reference evapotranspiration time series forecasting: A comparison of accuracy, complexity, and data efficiency
Reference evapotranspiration (ETo) is an essential variable in agricultural water resources
management and irrigation scheduling. An accurate and reliable forecast of ETo facilitates …
management and irrigation scheduling. An accurate and reliable forecast of ETo facilitates …
Advancing horizons in remote sensing: a comprehensive survey of deep learning models and applications in image classification and beyond
In recent years, deep learning has significantly reshaped numerous fields and applications,
fundamentally altering how we tackle a variety of challenges. Areas such as natural …
fundamentally altering how we tackle a variety of challenges. Areas such as natural …
[HTML][HTML] From roofs to renewables: Deep learning and geographic information systems insights into a comprehensive urban solar photovoltaic assessment for …
As urban solar photovoltaic (PV) construction emerges as a leading renewable energy
technology, there is a growing focus on its implementation. However, the challenges of …
technology, there is a growing focus on its implementation. However, the challenges of …
Automatic monitoring cheese ripeness using computer vision and artificial intelligence
Ripening is a very important process that contributes to cheese quality, as its characteristics
are determined by the biochemical changes that occur during this period. Therefore …
are determined by the biochemical changes that occur during this period. Therefore …
ResNet-SVM: Fusion based glioblastoma tumor segmentation and classification
Computerized segmentation of brain tumor based on magnetic resonance imaging (MRI)
data presents an important challenging act in computer vision. In image segmentation …
data presents an important challenging act in computer vision. In image segmentation …
Improved U-Net for growth stage recognition of in-field maize
T Wan, Y Rao, X Jin, F Wang, T Zhang, Y Shu, S Li - Agronomy, 2023 - mdpi.com
Precise recognition of maize growth stages in the field is one of the critical steps in
conducting precision irrigation and crop growth evaluation. However, due to the ever …
conducting precision irrigation and crop growth evaluation. However, due to the ever …
ResNeXt-SVM: a novel strawberry appearance quality identification method based on ResNeXt network and support vector machine
The identification of strawberry appearance quality is a crucial step to harvest fruits and can
assist robotic picking in modern agricultural production. Most convolutional neural network …
assist robotic picking in modern agricultural production. Most convolutional neural network …