Generative adversarial networks (GANs) for image augmentation in agriculture: A systematic review
In agricultural image analysis, optimal model performance is keenly pursued for better
fulfilling visual recognition tasks (eg, image classification, segmentation, object detection …
fulfilling visual recognition tasks (eg, image classification, segmentation, object detection …
Recent advances in intra-hour solar forecasting: A review of ground-based sky image methods
F Lin, Y Zhang, J Wang - International Journal of Forecasting, 2023 - Elsevier
As the penetration of solar energy generation into power systems keeps rising, intra-hour
solar forecasting (IHSF) is becoming increasingly important for the secure and economical …
solar forecasting (IHSF) is becoming increasingly important for the secure and economical …
[HTML][HTML] Advances in solar forecasting: Computer vision with deep learning
Renewable energy forecasting is crucial for integrating variable energy sources into the grid.
It allows power systems to address the intermittency of the energy supply at different …
It allows power systems to address the intermittency of the energy supply at different …
Cloud detection methodologies: Variants and development—A review
S Mahajan, B Fataniya - Complex & Intelligent Systems, 2020 - Springer
Cloud detection is an essential and important process in satellite remote sensing.
Researchers proposed various methods for cloud detection. This paper reviews recent …
Researchers proposed various methods for cloud detection. This paper reviews recent …
Open-source sky image datasets for solar forecasting with deep learning: A comprehensive survey
Sky image-based solar forecasting using deep learning has been recognized as a
promising approach in reducing the uncertainty of solar power generation. However, a major …
promising approach in reducing the uncertainty of solar power generation. However, a major …
[HTML][HTML] Using U-Net network for efficient brain tumor segmentation in MRI images
Abstract Magnetic Resonance Imaging (MRI) is the most commonly used non-intrusive
technique for medical image acquisition. Brain tumor segmentation is the process of …
technique for medical image acquisition. Brain tumor segmentation is the process of …
A 3D ConvLSTM-CNN network based on multi-channel color extraction for ultra-short-term solar irradiance forecasting
Due to the intermittency and fluctuation of solar energy, its exponential growth presents
serious challenges to the power system. Therefore, photovoltaic (PV) power forecasting …
serious challenges to the power system. Therefore, photovoltaic (PV) power forecasting …
Prediction of solar irradiance and photovoltaic solar energy product based on cloud coverage estimation using machine learning methods
Cloud cover estimation from images taken by sky-facing cameras can be an important input
for analyzing current weather conditions and estimating photovoltaic power generation. The …
for analyzing current weather conditions and estimating photovoltaic power generation. The …
SegCloud: A novel cloud image segmentation model using a deep convolutional neural network for ground-based all-sky-view camera observation
Cloud detection and cloud properties have substantial applications in weather forecast,
signal attenuation analysis, and other cloud-related fields. Cloud image segmentation is the …
signal attenuation analysis, and other cloud-related fields. Cloud image segmentation is the …
CloudSegNet: A deep network for nychthemeron cloud image segmentation
We analyze clouds in the earth's atmosphere using ground-based sky cameras. An accurate
segmentation of clouds in the captured sky/cloud image is difficult, owing to the fuzzy …
segmentation of clouds in the captured sky/cloud image is difficult, owing to the fuzzy …