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Total 109 results found since Jan 2013.

Sensors, Vol. 23, Pages 7766: Anthropogenic Object Localization: Evaluation of Broad-Area High-Resolution Imagery Scans Using Deep Learning in Overhead Imagery
We present algorithms for localizing object detection results, as well as a methodology for the evaluation of the results of broad-area scans. Our research explores the challenges of transitioning these models out of the training–validation laboratory setting and into the real-world application domain. We show a scalable approach to leverage state-of-the-art deep convolutional neural networks for the search, detection, and annotation of objects within large swaths of imagery, with the ultimate goal of providing a methodology for evaluating object detection machine learning models in real-world scenarios.
Source: Sensors - September 8, 2023 Category: Biotechnology Authors: J. Alex Hurt Ilinca Popescu Curt H. Davis Grant J. Scott Tags: Article Source Type: research

Sensors, Vol. 23, Pages 6806: On the Development of a Digital Twin for Underwater UXO Detection Using Magnetometer-Based Data in Application for the Training Set Generation for Machine Learning Models
eczorek Scanning underwater areas using magnetometers in search of unexploded ordnance is a difficult challenge, where machine learning methods can find a significant application. However, this requires the creation of a dataset enabling the training of prediction models. Such a task is difficult and costly due to the limited availability of relevant data. To address this challenge in the article, we propose the use of numerical modeling to solve this task. The conducted experiments allow us to conclude that it is possible to obtain high compliance with the numerical model based on the finite element method with the re...
Source: Sensors - July 30, 2023 Category: Biotechnology Authors: Marcin Blachnik Roman Przy łucki S ławomir Golak Piotr Ściegienka Tadeusz Wieczorek Tags: Article Source Type: research

Sensors, Vol. 23, Pages 6101: An Improved Distributed Sampling PPO Algorithm Based on Beta Policy for Continuous Global Path Planning Scheme
n Zhang Traditional path planning is mainly utilized for path planning in discrete action space, which results in incomplete ship navigation power propulsion strategies during the path search process. Moreover, reinforcement learning experiences low success rates due to its unbalanced sample collection and unreasonable design of reward function. In this paper, an environment framework is designed, which is constructed using the Box2D physics engine and employs a reward function, with the distance between the agent and arrival point as the main, and the potential field superimposed by boundary control, obstacles, and ar...
Source: Sensors - July 2, 2023 Category: Biotechnology Authors: Qianhao Xiao Li Jiang Manman Wang Xin Zhang Tags: Article Source Type: research

Sensors, Vol. 23, Pages 4402: extendGAN: Transferable Data Augmentation Framework Using WGAN-GP for Data-Driven Indoor Localisation Model+
Lye Oh For indoor localisation, a challenge in data-driven localisation is to ensure sufficient data to train the prediction model to produce a good accuracy. However, for WiFi-based data collection, human effort is still required to capture a large amount of data as the representation Received Signal Strength (RSS) could easily be affected by obstacles and other factors. In this paper, we propose an extendGAN+ pipeline that leverages up-sampling with the Dirichlet distribution to improve location prediction accuracy with small sample sizes, applies transferred WGAN-GP for synthetic data generation, and ensures data q...
Source: Sensors - April 30, 2023 Category: Biotechnology Authors: Seanglidet Yean Wayne Goh Bu-Sung Lee Hong Lye Oh Tags: Article Source Type: research

Sensors, Vol. 23, Pages 4402: extendGAN+: Transferable Data Augmentation Framework Using WGAN-GP for Data-Driven Indoor Localisation Model
Lye Oh For indoor localisation, a challenge in data-driven localisation is to ensure sufficient data to train the prediction model to produce a good accuracy. However, for WiFi-based data collection, human effort is still required to capture a large amount of data as the representation Received Signal Strength (RSS) could easily be affected by obstacles and other factors. In this paper, we propose an extendGAN+ pipeline that leverages up-sampling with the Dirichlet distribution to improve location prediction accuracy with small sample sizes, applies transferred WGAN-GP for synthetic data generation, and ensures data qu...
Source: Sensors - April 30, 2023 Category: Biotechnology Authors: Seanglidet Yean   Wayne Goh Bu-Sung Lee Hong Lye Oh Tags: Article Source Type: research

Sensors, Vol. 23, Pages 4383: Cluster-Locating Algorithm Based on Deep Learning for Silicon Pixel Sensors
In this study, we constructed and compared the performance of one-stage detection algorithms with the representative YOLO (You Only Look Once) framework and two-stage detection algorithms with an RCNN (region-based convolutional neural network). In addition, we also compared transformer-based backbones and CNN-based backbones. The dataset was obtained from a heavy-ion test on a Topmetal-M silicon pixel sensor at HIRFL. Heavy-ion tests were performed on the Topmetal-M silicon pixel sensor to establish the dataset for training and validation. In general, we achieved state-of-the-art results: 68.0% AP (average precision) at a...
Source: Sensors - April 28, 2023 Category: Biotechnology Authors: Fatai Mai Haibo Yang Dong Wang Gang Chen Ruxin Gao Xurong Chen Chengxin Zhao Tags: Article Source Type: research

Sensors, Vol. 23, Pages 4313: Vehicle Logo Recognition Using Spatial Structure Correlation and YOLO-T
aoyu Zhao The vehicle logo contains the vehicle’s identity information, so vehicle logo detection (VLD) technology has extremely important significance. Although the VLD field has been studied for many years, the detection task is still difficult due to the small size of the vehicle logo and the background interference problem. To solve these problems, this paper proposes a method of VLD based on the YOLO-T model and the correlation of the vehicle space structure. Aiming at the small size of the vehicle logo, we propose a vehicle logo detection network called YOLO-T. It integrates multiple receptive field...
Source: Sensors - April 27, 2023 Category: Biotechnology Authors: Li Song Weidong Min Linghua Zhou Qi Wang Haoyu Zhao Tags: Article Source Type: research

Sensors, Vol. 23, Pages 4259: Wearable Motion Capture Devices for the Prevention of Work-Related Musculoskeletal Disorders in Ergonomics & mdash;An Overview of Current Applications, Challenges, and Future Opportunities
Sensors, Vol. 23, Pages 4259: Wearable Motion Capture Devices for the Prevention of Work-Related Musculoskeletal Disorders in Ergonomics—An Overview of Current Applications, Challenges, and Future Opportunities Sensors doi: 10.3390/s23094259 Authors: Carl Mikael Lind Farhad Abtahi Mikael Forsman Work-related musculoskeletal disorders (WMSDs) are a major contributor to disability worldwide and substantial societal costs. The use of wearable motion capture instruments has a role in preventing WMSDs by contributing to improvements in exposure and risk assessment and potentially improved effectiveness in ...
Source: Sensors - April 25, 2023 Category: Biotechnology Authors: Carl Mikael Lind Farhad Abtahi Mikael Forsman Tags: Review Source Type: research

Sensors, Vol. 23, Pages 3960: Use, Validity and Reliability of Inertial Movement Units in Volleyball: Systematic Review of the Scientific Literature
rtega The use of inertial devices in sport has become increasingly common. The aim of this study was to examine the validity and reliability of multiple devices for measuring jump height in volleyball. The search was carried out in four databases (PubMed, Scopus, Web of Sciences and SPORTDiscus) using keywords and Boolean operators. Twenty-one studies were selected that met the established selection criteria. The studies focused on determining the validity and reliability of IMUs (52.38%), on controlling and quantifying external load (28.57%) and on describing differences between playing positions (19.05%). Indoor voll...
Source: Sensors - April 13, 2023 Category: Biotechnology Authors: Diego Hern án Villarejo-García Adri án Moreno-Villanueva Alejandro Soler-L ópez Pedro Reche-Soto Jos é Pino-Ortega Tags: Systematic Review Source Type: research

Sensors, Vol. 23, Pages 3942: SVR-Net: A Sparse Voxelized Recurrent Network for Robust Monocular SLAM with Direct TSDF Mapping
This study proposes a monocular SLAM system based on a sparse voxelized recurrent network, SVR-Net. It extracts voxel features from a pair of frames for correlation and recursively matches them to estimate pose and dense map. The sparse voxelized structure is designed to reduce memory occupation of voxel features. Meanwhile, gated recurrent units are incorporated to iteratively search for optimal matches on correlation maps, thereby enhancing the robustness of the system. Additionally, Gauss–Newton updates are embedded in iterations to impose geometrical constraints, which ensure accurate pose estimation. Aft...
Source: Sensors - April 13, 2023 Category: Biotechnology Authors: Rongling Lang Ya Fan Qing Chang Tags: Article Source Type: research

Sensors, Vol. 23, Pages 3714: Metaheuristic Optimization-Based Feature Selection for Imagery and Arithmetic Tasks: An fNIRS Study
This study presents a wrapper-based metaheuristic feature selection framework for BCI applications using functional near-infrared spectroscopy (fNIRS). Here, the temporal statistical features (i.e., the mean, slope, maximum, skewness, and kurtosis) were computed from all the available channels to form a training vector. Seven metaheuristic optimization algorithms were tested for their classification performance using a k-nearest neighbor-based cost function: particle swarm optimization, cuckoo search optimization, the firefly algorithm, the bat algorithm, flower pollination optimization, whale optimization, and grey wolf o...
Source: Sensors - April 3, 2023 Category: Biotechnology Authors: Amad Zafar Shaik Javeed Hussain Muhammad Umair Ali Seung Won Lee Tags: Article Source Type: research

Sensors, Vol. 23, Pages 1817: Efficacy of Specific Trunk Exercises in the Balance Dysfunction of Patients with Parkinson & rsquo;s Disease: A Systematic Review and Meta-Analysis
Sensors, Vol. 23, Pages 1817: Efficacy of Specific Trunk Exercises in the Balance Dysfunction of Patients with Parkinson’s Disease: A Systematic Review and Meta-Analysis Sensors doi: 10.3390/s23041817 Authors: Remedios López-Liria Sofía Vega-Tirado María Ángeles Valverde-Martínez Andrés Calvache-Mateo Ana María Martínez-Martínez Patricia Rocamora-Pérez Parkinson’s disease (PD) is a neurodegenerative pathology classified as a movement disorder. Physical exercise within a physiotherapy program is an important element to improve postural stability, balance and mobility in or...
Source: Sensors - February 6, 2023 Category: Biotechnology Authors: Remedios L ópez-Liria Sof ía Vega-Tirado Mar ía Ángeles Valverde-Martínez Andr és Calvache-Mateo Ana Mar ía Martínez-Martínez Patricia Rocamora-P érez Tags: Review Source Type: research

Sensors, Vol. 23, Pages 1811: An Improved CatBoost-Based Classification Model for Ecological Suitability of Blueberries
Tao Qin Selecting the best planting area for blueberries is an essential issue in agriculture. To better improve the effectiveness of blueberry cultivation, a machine learning-based classification model for blueberry ecological suitability was proposed for the first time and its validation was conducted by using multi-source environmental features data in this paper. The sparrow search algorithm (SSA) was adopted to optimize the CatBoost model and classify the ecological suitability of blueberries based on the selection of data features. Firstly, the Borderline-SMOTE algorithm was used to balance the number of positive...
Source: Sensors - February 6, 2023 Category: Biotechnology Authors: Wenfeng Chang Xiao Wang Jing Yang Tao Qin Tags: Article Source Type: research

Sensors, Vol. 23, Pages 1713: Neural Architecture Search Survey: A Computer Vision Perspective
g-Hoon Park In recent years, deep learning (DL) has been widely studied using various methods across the globe, especially with respect to training methods and network structures, proving highly effective in a wide range of tasks and applications, including image, speech, and text recognition. One important aspect of this advancement is involved in the effort of designing and upgrading neural architectures, which has been consistently attempted thus far. However, designing such architectures requires the combined knowledge and know-how of experts from each relevant discipline and a series of trial-and-error steps. In t...
Source: Sensors - February 3, 2023 Category: Biotechnology Authors: Jeon-Seong Kang JinKyu Kang Jung-Jun Kim Kwang-Woo Jeon Hyun-Joon Chung Byung-Hoon Park Tags: Review Source Type: research

Sensors, Vol. 23, Pages 1546: Small Sample Coherent DOA Estimation Method Based on S2S Neural Network Element Reinforcement Learning
ang Aiming at the existing Direction of Arrival (DOA) methods based on neural network, a large number of samples are required to achieve signal-scene adaptation and accurate angle estimation. In the coherent signal environment, the problems of a larger amount of training sample data are required. In this paper, the DOA of coherent signal is converted into the DOA parameter estimation of the angle interval of incident signal. The accurate estimation of coherent DOA under the condition of small samples based on meta−reinforcement learning (MRL) is realized. The meta−reinforcement learning meth...
Source: Sensors - January 31, 2023 Category: Biotechnology Authors: Zihan Wu Jun Wang Tags: Article Source Type: research