Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 19 of 19 for “"Activity Classification"”.
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On Quaternions and Activity Classification Across Sensor Domains
Activity classification based on sensor data is a challenging task. Many studies have focused on two main methods to enable activity classification; namely sensor level classification and body-model level classification. This study aims to enable activity classification across sensor domains by …
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Toward Practical, In-The-Wild, and Reusable Wearable Activity Classification
Wearable activity classifiers, so far, have been able to perform well with simple activities, strictly-scripted activities, and application-specific activities. In addition, current classification systems suffer from using impractical tight-fitting sensor networks, or only use one loose-fitting …
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Development and Assessment of Smart Textile Systems for Human Activity Classification
… An emerging technology for physical activity assessment is Smart Textile Systems (STSs), comprised of sensitive/actuating fiber, yarn, or fabric that can sense an external stimulus. All required components of an STS (sensors, electronics, energy supply, etc.) can be conveniently …
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Analyzing Activities and Events in Video From Motion Content
… algorithm is presented with application to video activity classification.
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Watching Humans and Detecting Their Abnormalities
… involves in human detection, human tracking, and activity classification, is discussed in the dissertation. The current system can only work under familiar environments. Future work will aim at a general abnormality detection system for video surveillance.
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Conectividade cerebral como característica para classificar tarefas motoras de mesmo segmento corporal: Interação humano-robô
Motor activity classification based on the Electroencephalogram (EEG) has been widely studied to assist brain-computer interfaces (BCIs). However, same limb motor activity classification still remains a challenge due to EEG close spatial representation on the motor cortex area in such case. Brain …
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Self-supervised Learning for IMU-based Human Activity Recognition
In recent years, human activity recognition has drawn considerable attention due to its application in a variety of areas such as smart homes and health. The pervasiveness of wearable devices and smartphones has provided many research opportunities for human activity recognition using inertial …
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AI-ML Powered Pig Behavior Classification and Body Weight Prediction
… livestock farming, this study focuses on activity classification and body weight prediction in pigs. Activity monitoring is essential for understanding the health and growth of pigs. To automate this task effectively, we propose efficient and accurate sensor-based deep learning (DL) …
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An Ambulatory Monitoring Algorithm to Unify Diverse E-Textile Garments
In this thesis, an activity classification algorithm is developed to support a human ambulatory monitoring system. This algorithm, to be deployed on an e-textile garment, represents the enabling step in creating a wide range of garments that can use the same classifier without having to re-train …
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Assessing activity energy expenditure from body-worn sensors during free-living
… sensors to objectively capture the physical activity of free-living individuals in large studies across the world. For research into metabolic diseases such as obesity and diabetes, it is useful to use this data to assess activity energy expenditure, which requires development of inference …
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Uncovering urban dynamics via cross-modal representation learning
… with massive GTSM data. After extracting activity-related tweets by measuring the dispersion degree of each keyword, CrossMap first employs an accelerated mode seeking procedure on all the extracted activity-related tweets to detect the spatiotemporal hotspots underlying people's …
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HUMAN ACTIVITY RECOGNITION FROM EGOCENTRIC VIDEOS AND ROBUSTNESS ANALYSIS OF DEEP NEURAL NETWORKS
… significant amount of research work on human activity classification relying either on Inertial Measurement Unit (IMU) data or data from static cameras providing a third-person view. There has been relatively less work using wearable cameras, providing egocentric view, which is a first-person …
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Computer Vision Algorithms for Mobile Camera Applications
… become more feasible to develop algorithms for activity monitoring, guidance and navigation of unmanned vehicles, autonomous driving and driver assistance, by using data from one or more of these sensors. In this thesis, we focus on multiple mobile camera applications, and present lightweight …
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Human Activity Analysis
… for tasks of regression, like body tracking, and activity classification.</p><p>We first consider activities that can be distinguished by their appearance during a single moment in time. Specifically, we use a database-retrieval approach to both approximate the full 3D pose of the hand from a …
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Ambulatory Fall Event Detection with Integrative Ambulatory Measurement (IAM) Framework
Injuries associated with fall accidents pose a significant health problem to society, both in terms of human suffering and economic losses. Existing fall intervention approaches are facing various limitations. This dissertation presented an effort to advance indirect type of injury prevention …
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Multimedia Content Analysis for Event Detection
… The automatic understanding of human activity is still an open problems in the scientific community, although several solutions have been proposed so far, and may provide important breakthroughs in many application domains such as context-aware computing, area monitoring and …
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Automatic feature extraction for time series analysis using deep and machine learning
… involved in time series analysis and classification for both industrial and Electrocardiogram (ECG) signals using deep learning approaches like CNNs, LSTMs and transformers etc. The analysis begins with a use case study of industrial collaboration with the lens manu- facturing industry …
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An Activity-Based Framework for Automated Placement and Configuration of Multiple Stereo Cameras
… several applications such as face recognition, activity classification, human tracking, etc. improves significantly from it. The quality of information depends on placement of stereo cameras and color constancy of scene appearance from multiple imaging devices. Thus, an important challenge in …
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Personal Big Data
… of spatio-temporal trajectory data, enriched by activity classification, as the input and foundation for the algorithmic model. The algorithmic model consists of three basal components: locations (vertices), trips (edges), and clusters (neighbourhoods). After preprocessing the incoming trajectory …