Publications by authors named "Haolin Liang"
Adaptive 3DCNN-based Interpretable Ensemble Model for Early Diagnosis of Alzheimer's Disease.
IEEE Trans Comput Soc Syst
February 2024
Article Synopsis
- A new model called 3DCNN+EL+GA combines three-dimensional convolutional neural networks and genetic algorithms to identify patients with Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) by analyzing brain images.
- The model not only classifies these conditions but also pinpoints specific brain regions involved, like the hippocampus and amygdala, that are crucial for emotions and memory.
- Testing on data from Alzheimer's Disease Neuroimaging Initiative (ADNI) and Open Access Series of Imaging Studies (OASIS) showed this method is more effective than other deep learning approaches, and future studies aim to explore its application for identifying brain regions in other disorders, such as depression and schizophrenia.
A Novel Calibration Board and Experiments for 3D LiDAR and Camera Calibration.
Sensors (Basel)
February 2020
Aiming at the problems of feature point calibration method of 3D light detection and ranging (LiDAR) and camera calibration that are calibration boards in various forms, incomplete information extraction methods and large calibration errors, a novel calibration board with local gradient depth information and main plane square corner information (BWDC) was designed. In addition, the "three-step fitting interpolation method" was proposed to select feature points and obtain the corresponding coordinates of feature points in the LiDAR coordinate system and camera pixel coordinate system based on BWDC. Finally, calibration experiments were carried out, and the calibration results were verified by methods such as incremental verification and reprojection error comparison.
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