Radar-based sensing emerges as a promising alternative to cameras and wearable devices for indoor human activity recognition. Unlike wearables, radar sensors offer non-contact and unobtrusive monitoring, while being i...
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ISBN:
(纸本)9781510673915;9781510673908
Radar-based sensing emerges as a promising alternative to cameras and wearable devices for indoor human activity recognition. Unlike wearables, radar sensors offer non-contact and unobtrusive monitoring, while being insensitive to lighting conditions and preserving privacy as compared to cameras. This paper addresses the task of continuous and sequential classification of daily life activities, unlike the problem to isolate distinct motions in isolation. Upon acquiring raw radar data containing sequences of motions, an event detection algorithm, the Short-Time-Average/Long-Time-Average (STA/LTA) algorithm, is utilized to detect individual motion segments. By recognizing breaks between transitions from one motion type to another, the STA/LTA detector isolates individual activity segments. To ensure consistent input shapes for activities of varying durations, image resizing and cropping techniques are employed. Furthermore, data augmentation techniques are applied to modify micro-Doppler signatures, enhancing the classification system's robustness and providing additional data for training.
image forgery has been a serious issue in real life during this boosting big data era. There have been many methods depending on detecting footprints such as edge inconsistency, camera noise, JPEG artifacts, etc., pro...
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Despite the widespread implementation of SCADA systems in factories for centralized data management, their functionality is restricted to devices equipped with sensors. Manual readings are still prevalent for critical...
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The proceedings contain 325 papers. The topics discussed include: significance and comparison of PCA in removing multicollinearity of variables in face detection and recognition;plant species classification using deep...
ISBN:
(纸本)9798350365092
The proceedings contain 325 papers. The topics discussed include: significance and comparison of PCA in removing multicollinearity of variables in face detection and recognition;plant species classification using deep learning;optimized local secret sharing techniques for distributed blockchain networks;NNXG: privacy based imageprocessing in pneumonia detection from chest x-ray using modified neural network architecture and XGBoost;a systematization of polycystic ovary syndrome using ultrasonography image follicle screening;automatic number plate recognition system using deep learning algorithms and imageprocessing for surveillance;ai-enhanced intelligent control systems for electric vehicles;and speculative analysis of CNN's and ResNet50 for the identification of emotion from facial expressions.
This paper delves into the groundbreaking potential of quantum computing, with a primary focus on qubits and their wide-ranging applications. It explores the fundamental principles of quantum physics, such as entangle...
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In response to the less referees in non -professional basketball events, this article will design a multi -functional basketball technology station based on deep learning gesture recognition and image -based car -base...
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One of the most frequent errors in UHVDC transmission systems is commutation failure. Following the commutation failure, the DC current will dramatically increase and DC voltage will abruptly decrease, which seriously...
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Artificial neural network (ANN) is an intelligent system that imitates the information processing mode of human brain nervous system. It is a simplification, abstraction and simulation of human brain ANN, which can be...
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Due to the severe attenuation, current remote sensing satellites cannot provide the required depth and resolution for subsurface detection. Spaceborne multistatic SAR tomography technology has the potential to fulfill...
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This study focuses on driver intention prediction models and their application to adaptive cruise control (ACC) system optimization. Through a deep learning approach, we built a highly accurate and stable prediction m...
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