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 …
Open-source ground-based sky image datasets for very short-term solar forecasting, cloud analysis and modeling: A comprehensive survey
Sky-image-based solar forecasting using deep learning has been recognized as a
promising approach in reducing the uncertainty in solar power generation. However, one of …
promising approach in reducing the uncertainty in solar power generation. However, one of …
SIFT-CNN: when convolutional neural networks meet dense SIFT descriptors for image and sequence classification
Despite the success of hand-crafted features in computer visioning for many years,
nowadays, this has been replaced by end-to-end learnable features that are extracted from …
nowadays, this has been replaced by end-to-end learnable features that are extracted from …
A novel method for ground-based cloud image classification using transformer
X Li, B Qiu, G Cao, C Wu, L Zhang - Remote Sensing, 2022 - mdpi.com
In recent years, convolutional neural networks (CNNs) have achieved competitive
performance in the field of ground-based cloud image (GCI) classification. Proposed CNN …
performance in the field of ground-based cloud image (GCI) classification. Proposed CNN …
UATNet: U-shape attention-based transformer net for meteorological satellite cloud recognition
Cloud recognition is a basic task in ground meteorological observation. It is of great
significance to accurately identify cloud types from long-time-series satellite cloud images for …
significance to accurately identify cloud types from long-time-series satellite cloud images for …
[HTML][HTML] Enhancing Human Activity Recognition through Integrated Multimodal Analysis: A Focus on RGB Imaging, Skeletal Tracking, and Pose Estimation
Human activity recognition (HAR) is pivotal in advancing applications ranging from
healthcare monitoring to interactive gaming. Traditional HAR systems, primarily relying on …
healthcare monitoring to interactive gaming. Traditional HAR systems, primarily relying on …
Voting in transfer learning system for ground-based cloud classification
Cloud classification is a great challenge in meteorological research. The different types of
clouds, currently known and present in our skies, can produce radioactive effects that impact …
clouds, currently known and present in our skies, can produce radioactive effects that impact …
Ground-based remote sensing cloud classification via context graph attention network
Most ground-based remote sensing cloud classification methods focus on learning
representation features for cloud images while ignoring the correlations among cloud …
representation features for cloud images while ignoring the correlations among cloud …
STANet: a novel predictive neural network for Ground-based remote sensing cloud image sequence extrapolation
Z Lu, Z Zhou, X Li, J Zhang - IEEE Transactions on Geoscience …, 2023 - ieeexplore.ieee.org
Cloud image sequence extrapolation plays an important role in ground-based remote
sensing observation because allows the observation range to be extended in the …
sensing observation because allows the observation range to be extended in the …
MMST: A Multi-Modal Ground-Based Cloud Image Classification Method
L Wei, T Zhu, Y Guo, C Ni - Sensors, 2023 - mdpi.com
In recent years, convolutional neural networks have been in the leading position for ground-
based cloud image classification tasks. However, this approach introduces too much …
based cloud image classification tasks. However, this approach introduces too much …