34 citations · 65 across the 7 of their papers we have counts for
8 papers
Optical Wavelength Guided Self-Supervised Feature Learning For Galaxy Cluster Richness Estimate
Gongbo Liang, Yuanyuan Su, Sheng-Chieh Lin +3
Most galaxies in the nearby Universe are gravitationally bound to a cluster or group of galaxies. Their optical contents, such as optical richness, are crucial for understanding th…
Dynamic Image for 3D MRI Image Alzheimer's Disease Classification
Xin Xing, Gongbo Liang, Hunter Blanton +4
We propose to apply a 2D CNN architecture to 3D MRI image Alzheimer's disease classification. Training a 3D convolutional neural network (CNN) is time-consuming and computationally…
Improved Trainable Calibration Method for Neural Networks on Medical Imaging Classification
Gongbo Liang, Yu Zhang, Xiaoqin Wang +1
Recent works have shown that deep neural networks can achieve super-human performance in a wide range of image classification tasks in the medical imaging domain. However, these wo…
A deep learning view of the census of galaxy clusters in IllustrisTNG
Y. Su, Y. Zhang, G. Liang +8
The origin of the diverse population of galaxy clusters remains an unexplained aspect of large-scale structure formation and cluster evolution. We present a novel method of using X…
Unsupervised Domain Adaptation for Mammogram Image Classification: A Promising Tool for Model Generalization
Yu Zhang, Gongbo Liang, Nathan Jacobs +1
Generalization is one of the key challenges in the clinical validation and application of deep learning models to medical images. Studies have shown that such models trained on pub…
Joint 2D-3D Breast Cancer Classification
Gongbo Liang, Xiaoqin Wang, Yu Zhang +4
Breast cancer is the malignant tumor that causes the highest number of cancer deaths in females. Digital mammograms (DM or 2D mammogram) and digital breast tomosynthesis (DBT or 3D…