Human activity recognition (HAR) using wearable sensors is always a research hotspot in
ubiquitous computing scenario, in which feature learning has played a crucial role. Recent …

Deep supervision, which involves extra supervisions to the intermediate features of a neural
network, was widely used in image classification in the early deep learning era since it …

Plant leaf disease classification is an important task in smart agriculture which plays a critical
role in sustainable production. Modern machine learning approaches have shown …

Background Despite extensive efforts to obtain accurate segmentation of magnetic
resonance imaging (MRI) scans of a head, it remains challenging primarily due to variations …

Numerous point-cloud understanding techniques focus on whole entities and have
succeeded in obtaining satisfactory results and limited sparsity tolerance. However, these …

Background Autosomal dominant polycystic kidney disease (ADPKD) can lead to polycystic
liver disease (PLD), characterized by liver cysts. Although majority of the patients are …

This dissertation represents the work I did in integrating advanced machine learning
techniques into three important challenges that the field of astronomy currently faces. Firstly …

Neuroimaging importance for stroke is growing widely. The difficulty of quantifying and
describing ischemic stroke lesions is yet an unsolved and semi-automated time-consuming …

Purpose: Accurate segmentation of brain tumors is critical for patient treatment and
prognosis. The purpose of this study is to demonstrate different Training strategies to train …