Indoor human tracking and activity recognition are fundamental yet coherent problems for ambient assistive living. In this paper, we propose a method to address these two critical issues simultaneously. We construct a wireless sensor network (WSN), a...
Hand gesture recognition from images is a critical task with various real-world applications, particularly in the field of human–robot interaction. Industrial environments, where non-verbal communication is preferred, are significant areas of a...
Indoor localization and human activity recognition are two important sources of information to provide context-based assistance. This information is relevant in ambient assisted living (AAL) scenarios, where older adults usually need supervision and...
Two-dimensional (2D) MXenes have shown a great potential for chemical sensing due to their electric properties. In this work, a Ti3C2Tx/polypyrrole (MXene/PPy) nanocomposite has been synthesized and immobilized into a glassy carbon electrode to enabl...
In this study, a methodology for automatic recognition of multiple simultaneous types of partial discharges (PDs) in hydro-generator stator windings was proposed. All the seven PD sources typical in rotating machines were considered, and up to three...
In this paper, we propose a novel approach that enables simultaneous localization, mapping (SLAM) and objects recognition using visual sensors data in open environments that is capable to work on sparse data point clouds. In the proposed algorithm th...
The integration of robotics in the garment industry remains relatively limited, primarily due to the challenges in the highly deformable nature of garments. The objective of this study is thus to explore a vision-based garment recognition and environ...
With the recent advances of deep learning, automatic target recognition (ATR) of synthetic aperture radar (SAR) has achieved superior performance. By not being limited to the target category, the SAR ATR system could benefit from the simultaneous ext...
Facial expression recognition is crucial for understanding human emotions and nonverbal communication. With the growing prevalence of facial recognition technology and its various applications, accurate and efficient facial expression recognition has...
To solve the problem of multiple sound recognition in the application of Sagnac optical fiber acoustic sensing system, a multi-source synchronous recognition algorithm was proposed, which combined the VMD (variational modal decomposition) algorithm a...
Both three-dimensional (3D) object recognition and pose estimation are open topics in the research community. These tasks are required for a wide range of applications, sometimes separately, sometimes concurrently. Many different algorithms have been...
Speaking and eating are essential components of health management. To enable the daily monitoring of these behaviors, systems capable of simultaneously recognizing speech and eating behaviors are required. However, due to the distinct acoustic and co...
Discretization and feature selection are two relevant techniques for dimensionality reduction. The first one aims to transform a set of continuous attributes into discrete ones, and the second removes the irrelevant and redundant features; these two...
Simultaneous molecular recognition and quantification of at least four biomarkers in biological samples may contribute to early and fast diagnosis of illnesses such as cancer. The electrodes able to reliably perform on-site these tests are the stocha...
Adenosine phosphates (adenosine 5′-monophosphate (AMP), adenosine 5′-diphosphate (ADP), and adenosine 5′-triphosphate (ATP)) play important roles in energy storage and signal transduction in the human body. Thus, a measurement metho...
The automatic recognition of surgical gestures and the assessment of surgical skills are essential for improving patient safety and optimizing surgical training processes. In this paper, a shared spatiotemporal multitask learning framework for joint...
Place recognition is an essential part of simultaneous localization and mapping (SLAM). LiDAR-based place recognition relies almost exclusively on geometric information. However, geometric information may become unreliable when faced with environment...
This paper designed a voice interactive robot system that can conveniently execute assigned service tasks in real-life scenarios. It is equipped without a microphone where users can control the robot with spoken commands; the voice commands are then...
Heavy metal ions are common environmental contaminants that threaten aquatic ecosystems and human health. However, conventional analytical techniques often require expensive instrumentation and complex sample pretreatment. This work presents a peptid...
Low-latency visual perception is essential for interactive machine vision on edge AI devices, but conventional frame-based image sensors impose frame period delays and generate dense image data that increase memory bandwidth and processing latency. A...
Since light propagation in a multimode fiber (MMF) exhibits visually random and complex scattering patterns due to external interference, this study numerically models temperature and curvature through the finite element method in order to understand...
The formation of inclusion complexes between alkylsulfonate guests and a cationic pillar[5]arene receptor in water was investigated by NMR and ITC techniques. The results show the formation of host-guest complexes stabilized by electrostatic interact...
The Azure Kinect is the successor of Kinect v1 and Kinect v2. In this paper we perform brief data analysis and comparison of all Kinect versions with focus on precision (repeatability) and various aspects of noise of these three sensors. Then we thor...
The aim of this study was to devise a methodology for the on-site evaluation of the potential presence of persistent organic pollutants (POPs) in incoming waste materials. A novel approach to POP screening was developed, integrating an excitation&nda...
Crop maturity detection and yield estimation are critical components of protected agriculture, supporting optimized harvest timing, fruit quality control, and coordination of production and marketing. Existing studies on detection and counting predom...
It is a widely held belief that developmental dyslexia (DD) is a phonological disorder in which readers have difficulty associating graphemes with their corresponding phonemes. In contrast, the magnocellular theory of dyslexia assumes that DD is a vi...
Conventional surveillance for a security robot suffers from severe limitations, perceptual aliasing (e.g., different places/objects can appear identical), occlusion (e.g., place/object appearance changes between visits), illumination changes, signifi...
LiDAR loop closure detection is a key technology to mitigate localization drift in LiDAR SLAM, but it remains challenging in structurally similar environments and memory-constrained platforms. This paper proposes VS-SLAM, a novel and robust SLAM syst...
Seniors face many challenges as they age, such as dementia, cognitive and memory disorders, vision and hearing impairment, among others. Although most of them would like to stay in their own homes, as they feel comfortable and safe, in some cases, ol...
Traditional simultaneous localization and mapping (SLAM) system tends to operate in small-area static environments, and its performance might degrade when moving objects appear in a highly dynamic environment. To address this issue, this paper propos...
Reading involves many different abilities that are necessary or sufficient conditions for fluent and flawless reading. The absence of one necessary or of all sufficient conditions is a cause of dyslexia. The present study investigates whether too sho...
In recent decades, theories have been presented to explain the nature of dyslexia, but the causes of dyslexia remained unclear. Although the investigation of the causes of dyslexia presupposes a clear understanding of the concept of cause, such an un...
In dynamic environments, Simultaneous Localization and Mapping (SLAM) systems often struggle with the challenges posed by moving objects. To address these issues, we propose Dynamic-Object-Elimination LiDAR-Visual-Inertial SLAM (DOE-LVI), an advanced...
LiDAR-based place recognition is critical for long-term autonomous navigation in Global Navigation Satellite System (GNSS)-denied environments, yet existing methods struggle to balance accuracy and efficiency under substantial yaw rotations. This pap...
Small target features are difficult to distinguish and identify in an environment with complex backgrounds. The identification and extraction of multi-dimensional features have been realized due to the rapid development of deep learning, but there ar...
The scarcity of underwater acoustic data in deep and remote sea environments poses a significant challenge to data-driven target recognition models, severely restricting their performance. To address this challenge, this study presents a ray-theory-b...
In this paper, a multiple-input multiple-output reservoir computing (RC) system is proposed, which is composed of multiple nonlinear nodes (Mach–Zehnder modulators) and multiple mutual-coupling loops of optoelectronic delay lines. Each input si...
Cleaning loss is an important parameter to judge the performance of a corn combine harvester. At present, there exists the phenomenon that corn cleaning loss rate detection devices have a long signal processing time and low recognition accuracy. To s...
The rapid detection of petroleum hydrocarbons and organic pesticides is an important prerequisite for precise soil management. It is also a guarantee for soil quality, environmental safety, and human health. However, the current rapid detection metho...
Accurate identification of individual cattle is of paramount importance in precision livestock farming, enabling the monitoring of cattle behavior, disease prevention, and enhanced animal welfare. Unlike human faces, the faces of most Hanwoo cattle,...
In-sensor computing can simultaneously output image information and recognition results through in-situ visual signal processing, which can greatly improve the efficiency of machine vision. However, in-sensor computing is challenging due to the requi...
Dental X-ray images are important and useful for dentists to diagnose dental diseases. Utilizing deep learning in dental X-ray images can help dentists quickly and accurately identify common dental diseases such as periodontitis and dental caries. Th...
Existing public domain multi-modal datasets for human action recognition only include actions of interest that have already been segmented from action streams. These datasets cannot be used to study a more realistic action recognition scenario where...
Wearable and accompanied sensors and devices are increasingly being used for user activity recognition. However, typical GPS-based and accelerometer-based (ACC) methods face three main challenges: a low recognition accuracy; a coarse recognition capa...
Multi-attribute recognition is one of the main topics attaining much attention in the pattern recognition field these days. The conventional approaches to multi-attribute recognition has mainly focused on developing an individual classifier for each...
Hand gesture recognition and hand pose estimation are two closely correlated tasks. In this paper, we propose a deep-learning based approach which jointly learns an intermediate level shared feature for these two tasks, so that the hand gesture recog...
We investigated machine learning-based joint banknote recognition and counterfeit detection method. Unlike existing methods, since the proposed method simultaneously recognize banknote type and detect counterfeit detection, it is significantly faster...
Human activity recognition is a critical task for various applications across healthcare, sports, security, gaming, and other fields. This paper presents BodyFlow, a comprehensive library that seamlessly integrates human pose estimation and multiple-...
Anti-jamming is the core issue of wireless communication viability in complex electromagnetic environments, where jamming recognition is the precondition and foundation of cognitive anti-jamming. In the current jamming recognition methods, the existi...
Facial expressions help in understanding the intentions of others as they are an essential means of communication, revealing human emotions. Recently, thermal imaging has been playing a complementary role in emotion recognition and is considered an a...
of 24