Doi Thi Lan

A multi-branch network for cooperative spectrum sensing via attention-based and CNN feature fusion

Doi Thi Lan, Quan T. Ngo, Luong Vuong Nguyen, O‐Joun Lee

In cognitive radio (CR) systems, the accurate detection of spectrum holes is a cornerstone for efficient spectrum utilization. However, the increasing complexity of CR environments, particularly those with multiple primary users (PUs), has made precise spectrum sensing a paramount challenge. To address …

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Hierarchical Deep Learning for Multi-PU Cooperative Spectrum Sensing: A Sequential 1D-CNN and GCN Framework for Robust Feature Learning

Quan T. Ngo, Doi Thi Lan

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Cooperative Spectrum Sensing Based on Deep Learning and Clustering in Cognitive Radio

Quang Tran Minh, Doi Thi Lan

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A Novel Hierarchical Framework for Cooperative Spectrum Sensing using CNN and SVM

Doi Thi Lan, Hanh Phan Trong, Quan T. Ngo

Efficient dynamic spectrum access is essential in cognitive radio networks (CRNs) to alleviate spectrum scarcity. Cooperative spectrum sensing (CSS) plays a crucial role in detecting available spectrum by aggregating information from multiple secondary users (SUs). Although deep learning (DL) has significantly advanced …

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Anomalous Human Trajectory Detection Using Clustering Methods

Doi Thi Lan, Seokhoon Yoo

Anomalous human trajectory detection is a critical task in security surveillance in working places. Many studies have been proposed and achieved specific results in abnormal trajectory detection over recent years. In this paper, a framework is proposed for detecting anomalies in human …

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Trajectory Clustering-Based Anomaly Detection in Indoor Human Movement

Doi Thi Lan, Seokhoon Yoon

Human movement anomalies in indoor spaces commonly involve urgent situations, such as security threats, accidents, and fires. This paper proposes a two-phase framework for detecting indoor human trajectory anomalies based on density-based spatial clustering of applications with noise (DBSCAN). The first phase …

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Anomalous Indoor Human Trajectory Detection Based on the Transformer Encoder and Self-Organizing Map

Doi Thi Lan, Seokhoon Yoon

Anomalous human trajectory detection is a critical task in security surveillance in working areas. To identify anomalous human trajectories, understanding features of their movement plays an important role. Therefore, in this work, a Transformer encoder and self-organizing map-based model called TENSO is …

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Companion Mobility to Assist in Future Human Location Prediction

Quan T. Ngo, Doi Thi Lan, Seokhoon Yoon, Woo-Sung Jung et autres

Location prediction plays an important role in modeling human mobility. Existing studies focused on developing a prediction model which is based solely on the past mobility of only the person of interest (POI), rather than including information on the mobility of her/his …

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Proposal of Geometric Method for Drone Localization with Systems of Multiple Directional Antennas

Doi Thi Lan, Nguyen Minh Tuan, Phạm Thanh Hiệp

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