Learning hierarchical time series data augmentation invariances via contrastive supervision for human activity recognition
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 …
ubiquitous computing scenario, in which feature learning has played a crucial role. Recent …
Deepmim: Deep supervision for masked image modeling
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 …
network, was widely used in image classification in the early deep learning era since it …
Multi-output deep-supervised classifier chains for plant pathology
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 …
role in sustainable production. Modern machine learning approaches have shown …
Study of multistep Dense U‐Net‐based automatic segmentation for head MRI scans
Background Despite extensive efforts to obtain accurate segmentation of magnetic
resonance imaging (MRI) scans of a head, it remains challenging primarily due to variations …
resonance imaging (MRI) scans of a head, it remains challenging primarily due to variations …
Joint Learning for Scattered Point Cloud Understanding with Hierarchical Self-Distillation
K Zhou, M Dong, P Zhi, S Wang - arXiv preprint arXiv:2312.16902, 2023 - arxiv.org
Numerous point-cloud understanding techniques focus on whole entities and have
succeeded in obtaining satisfactory results and limited sparsity tolerance. However, these …
succeeded in obtaining satisfactory results and limited sparsity tolerance. However, these …
Deep learning-based liver cyst segmentation in MRI for autosomal dominant polycystic kidney disease
M Chookhachizadeh Moghadam, M Aspal… - Radiology …, 2024 - academic.oup.com
Background Autosomal dominant polycystic kidney disease (ADPKD) can lead to polycystic
liver disease (PLD), characterized by liver cysts. Although majority of the patients are …
liver disease (PLD), characterized by liver cysts. Although majority of the patients are …
Skyward AI: Advancing Astronomy with Intelligent Machines
S Bialek - 2023 - dspace.library.uvic.ca
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 …
techniques into three important challenges that the field of astronomy currently faces. Firstly …
3D Auto Segmentation Module for Ischemic Stroke Lesions from MONAI
E Ruthra, AR Bevi - … on Advances in Electrical, Electronics and …, 2023 - ieeexplore.ieee.org
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 …
describing ischemic stroke lesions is yet an unsolved and semi-automated time-consuming …
[PDF][PDF] Training Strategies for Brain Tumor Segmentation in 3D Volumetric Data: The Pipelines Approach to the BraTS 2020 Challenge
AWY E'layan, A Almakhadmeh - researchgate.net
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 …
prognosis. The purpose of this study is to demonstrate different Training strategies to train …