LSCB: a lightweight feature extraction block for SAR automatic target recognition and detection
G Zhou, J Yu, S Zhou - International Journal of Remote Sensing, 2023 - Taylor & Francis
Automatic target recognition and detection in synthetic aperture radar (SAR) images is
playing a significant role in military and civilian fields. Traditional methods are weak in …
playing a significant role in military and civilian fields. Traditional methods are weak in …
Shuffle-ResNet: Deep learning for predicting LGG IDH1 mutation from multicenter anatomical MRI sequences
Background and Purpose. The world health organization recommended to incorporate gene
information such as isocitrate dehydrogenase 1 (IDH1) mutation status to improve …
information such as isocitrate dehydrogenase 1 (IDH1) mutation status to improve …
Transforming Observations of Ocean Temperature with a Deep Convolutional Residual Regressive Neural Network
Sea surface temperature (SST) is an essential climate variable that can be measured via
ground truth, remote sensing, or hybrid model methodologies. Here, we celebrate SST …
ground truth, remote sensing, or hybrid model methodologies. Here, we celebrate SST …
A Model of Precise Delivery of Advertising based on Encrypted Transmission in Network
Y Wang, Y Fu, L Xu, X Ye - 2024 IEEE International …, 2024 - ieeexplore.ieee.org
Telecommunications (Telelcom) operators and Internet companies can effectively improve
the advertising delivery effectiveness and user experience by using their own user basic …
the advertising delivery effectiveness and user experience by using their own user basic …
Reduce Overfitting and Improve Deep Learning Models' Performance in Medical Image Classification
N Raju, DP Augustine - Machine Intelligence, 2023 - taylorfrancis.com
A significant role in clinical treatment and educational tasks is played by clinical image
classification. However, the traditional approach has reached its peak in terms of …
classification. However, the traditional approach has reached its peak in terms of …