过去一年中添加的文章，按日期排序
A Hybrid Model for Ultra-short-term PV Prediction Using SOM Clustering and ECA
Y Zhu, Z Wang, W Zhang, Y Liu, H Wu - 2024 - researchsquare.com
6 天前 - … using a Self-Organizing Map (SOM) neural network is … to focus on key feature
information and increase prediction … of feature information that the CNN has extracted. Lastly, the …
information and increase prediction … of feature information that the CNN has extracted. Lastly, the …
Integrating self-organizing feature map with graph convolutional network for enhanced superpixel segmentation and feature extraction in non-Euclidean data structure
YZ Hsieh, CH Wu, YT Chen - Multimedia Tools and Applications, 2024 - Springer
10 天前 - … of self-organizing feature maps for superpixel segmentation combined with graph
convolutional networks to … deep neural networks, convolutional neural networks, and others. …
convolutional networks to … deep neural networks, convolutional neural networks, and others. …
A Human-Like Visual Perception System for Autonomous Vehicles Using a Neuron-Triggered Hybrid Unsupervised Deep Learning Method
16 天前 - … The proposed approach (CAE-SOM) was a neuron… (CAE) and a self-organizing
map (SOM) neural network. The CAE … to extract the high-level features, whilst the SOM neural …
map (SOM) neural network. The CAE … to extract the high-level features, whilst the SOM neural …
EEG Emotion Recognition Network Based on Attention and Spatiotemporal Convolution
X Zhu, C Liu, L Zhao, S Wang - Sensors, 2024 - mdpi.com
38 天前 - … extract the spatial information of the encoded EEG signal [18]. The results demonstrate
that the neural network … This paper uses a self-organizing graph structure to explore the …
that the neural network … This paper uses a self-organizing graph structure to explore the …
Spectrum Sensing Based on Stochastic Resonance and SOM Neural Network
J He, B Zheng, Y Wang - 2024 16th International Conference on …, 2024 - ieeexplore.ieee.org
49 天前 - … stochastic resonance and selforganizing map (SOM) neural network (MSRSOM)
is … matrices are extracted as signal features. Finally, the SOM neural network is trained for …
is … matrices are extracted as signal features. Finally, the SOM neural network is trained for …
A hybrid model based on unsupervised learning for seismic response feature extraction and gas-bearing reservoir prediction using longitudinal and transverse waves …
K Zhang, N Lin, J Yang, C Fu, D Zhang - Journal of Applied Geophysics, 2024 - Elsevier
64 天前 - … redundant information, … self-organizing neural network (SOM) for unsupervised
learning. Neurons in the SOM compete with each other to optimize their own features and extract …
learning. Neurons in the SOM compete with each other to optimize their own features and extract …
Using Numerical Simulation and Artificial Neural Networks to Investigate the Influenc...
YY Ku - advance.sagepub.com
69 天前 - … flood inundation artifical neural networks numerical simulation self-organizing map
… for evaporation estimation by self-organizing map neural network. Journal of Hydrology, 384(…
… for evaporation estimation by self-organizing map neural network. Journal of Hydrology, 384(…
[HTML][HTML] A Hierarchical Heuristic Architecture for Unmanned Aerial Vehicle Coverage Search with Optical Camera in Curve-Shape Area
L Liu, D Wang, J Yu, P Yao, C Zhong, D Fu - Remote Sensing, 2024 - mdpi.com
71 天前 - … The rolling self-organizing map (RSOM) neural network is … prior information, the
curve-shaped area should be modeled and several high-value curve segments can be extracted…
curve-shaped area should be modeled and several high-value curve segments can be extracted…
Motor Imagery Classification Using Single Channel of EEG in Online Brain-Computer Interface
M Taghizadeh, A Chalechale - 2024 10th International …, 2024 - ieeexplore.ieee.org
71 天前 - … self-organizing maps (SOM) based on neural networks is … Sridhar and Manian
developed a deep learning network to … neural network (DCNN) can also be used to extract spatial …
developed a deep learning network to … neural network (DCNN) can also be used to extract spatial …
Detecting Network Anomalies Using the Rain Optimization Algorithm and Hoeffding Tree-based Autoencoder
MA Mohammad, M Kolahkaj - 2024 10th International …, 2024 - ieeexplore.ieee.org
71 天前 - … network detection, recognizing the critical importance of detecting anomalies in
extracting crucial information … high-dimensional spaces through neural networks and learning a …
extracting crucial information … high-dimensional spaces through neural networks and learning a …