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IMAGE QUANTIZATION TOWARDS DATA REDUCTION: ROBUSTNESS ANALYSIS FOR SLAM METHODS ON EMBEDDED PLATFORMS 29

IMAGE QUANTIZATION TOWARDS DATA REDUCTION: ROBUSTNESS ANALYS...

引用

IEEE International conference on Image processing (ICIP)

作者： Picard, Quentin Chevobbe, Stephane Darouich, Mehdi Didier, Jean-Yves CEA LIST F-91191 Gif Sur Yvette France Univ Paris Saclay Univ Evry IBISC F-91025 Evry France

ISBN: (数字)9781665496209

ISBN: (纸本)9781665496209

Embedded simultaneous localization and mapping (SLAM) aims at providing real-time performances with restrictive hardware resources of advanced perception functions. Localization methods based on visible cameras include image processing functions that require frame memory management. This work reduces the dynamic range of input frame and evaluates the accuracy and robustness of real-time SLAM algorithms with quantified frames. We show that the input data can be reduced up to 62% and 75% while maintaining a similar trajectory error lower than 0.15m compared to full precision input images.

关键词： SLAM localization image processing embedded systems real-time frame reduction

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SMD Coincident Antenna Array for 2D Field Acquisition and Reconstruction

SMD Coincident Antenna Array for 2D Field Acquisition and Re...

引用

International conference on Electromagnetics in advanced Applications (ICEAA)

作者： Francesca Ortolani Ironbridge Electronics Rome Italy

ISBN: (数字)9798350360974

ISBN: (纸本)9798350360981

Field acquisition and reconstruction by means of (near-)coincident arrays is quite consolidated in acoustics. Techniques such as Mid-Side, XY and Ambisonics, supported by algorithms for signal processing, paved the way to 2-dimensional and 3-dimensional sound recording and field synthesis, by placing microphones very close to each other in a single spot. On the other hand, the use of antenna coincident arrays for electromagnetic field acquisition is quite rare. This article proposes a preliminary study on the feasibility of coincident antenna arrays by means of surface mounted miniature chip antennas and the application of a 2-dimensional field acquisition technique such as Mid-Side to electromagnetism.

关键词： Phased arrays Three-dimensional displays Array signal processing Surface mount technology signal processing algorithms Radar Radar antennas Recording Electromagnetics Antenna arrays

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Prediction and Optimisation Models for Carbon Trading Prices - A Study Based on BP Neural Networks and Genetic algorithms

Prediction and Optimisation Models for Carbon Trading Prices...

引用

signal processing, Communications and Engineering Management conference (ISPCEM), International

作者： Jiayang Shen Anhui University of Finance and Economics Bengbu China

ISBN: (数字)9798331528676

ISBN: (纸本)9798331528683

This paper proposes a novel framework for an in-depth examination of carbon storage, integrating a genetic algorithm-backpropagation (GA-BP) approach with a greedy algorithm, based on empirical research into the optimization methods that combine genetic algorithms, neural networks, and greedy algorithms. A carbon prediction model utilizing a BP neural network is developed, focusing on domestic and international indicators, technical indicators, and exchange rates, alongside lagging macro indicators. Additionally, an optimization model for carbon storage prediction is established using a GA-BP neural network, enhanced and advanced through the LSTM method. The findings indicate that the model exhibits substantial robustness and attains relatively stable performance across varied market conditions, thereby enhancing efficiency and accuracy, fostering further advancements in carbon storage, offering strategic guidance for producers, and advancing traditional carbon storage towards a more efficient, transparent, and intelligent future.

关键词： Greedy algorithms Optimization models Neural networks signal processing algorithms signal processing Predictive models Prediction algorithms Robustness Carbon Genetic algorithms

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Diverse Image processing Techniques for Machine Learning Methods

Diverse Image Processing Techniques for Machine Learning Met...

引用

IEEE International conference on Intelligent Techniques in Control, Optimization and signal processing (INCOS)

作者： A. Bhagya S. Perumal Department of Computer Science Vels Institute of science Technology and Advanced Studies Chennai Tamil Nadu India

ISBN: (数字)9798350361186

ISBN: (纸本)9798350361193

Machine learning is a trending topic in the area of computer vision, which makes the machine able to learn about it without being expressly programmed using various algorithms. When a model is designed to predict future-based on historical data using machine learning algorithms, data is vital because high quality data is needed to run the model efficiently and to predict highly accurate results. Machine learning algorithms receive data in many forms, like audio (speech recognition), images (feature recognition), numeric data (like height and weight) etc. When it comes to computer vision, the machine learning algorithms must be able to understand the image data, and before the images are processed to the algorithms it should be pre-processed (cleaned and set to the desired format) using various image pre-processing techniques. This research paper presents various image processing techniques, literature reviews on various image processing techniques and image PSNR value after applying median filter, grayscale filter and box filters.

关键词： Machine learning algorithms Image processing signal processing algorithms Speech recognition Machine learning Gray-scale Filtering algorithms

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RoPE-BAM: Nested Entity Recognition Based on Rotary Position Embedding and Biaffine Attention Mechanism 3

RoPE-BAM: Nested Entity Recognition Based on Rotary Position...

引用

3rd International conference on advanced algorithms and Neural Networks, AANN 2023

作者： Deng, Jinxin Qin, Xizhong Yang, Rong Lv, Xiaoyi School of Information Science and Engineering Xinjiang University of China Xinjiang Key Laboratory of Signal Detection and Processing Urumqi830017 China The Fifth Affiliated Hospital of Xinjiang Medical Urumqi830017 China

ISBN: (纸本)9781510668355

Named entity recognition (NER) involves two main types: nested NER and flat NER. The span-based approach classifies entity types by head-tail pair span representations and can handle nested and flat entities uniformly. However, the span-based approach uses a single feature and ignores the relative position information between head-tail pairs, which affects the precision of entity recognition. Therefore, we propose a nested entity recognition model that combines rotary position embedding and biaffine attention mechanism (RoPE-BAM) to improve the model performance by adding relative position features to the span representations. Concretely, we first obtain the head sequence and tail sequence representations through two feedforward networks. Then, to incorporate the relative position features, rotary position embedding is applied to both head and tail sequences. Finally, we use a biaffine attention mechanism to capture the span representations while generating the relative position information in the span. Extensive experiments were conducted on five widely-used benchmark datasets to demonstrate the effectiveness of our proposed RoPE-BAM model. © 2023 SPIE.

关键词： Embeddings

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Bluetooth AOA Localization Technology Based on LS and MUSIC algorithms 23

Bluetooth AOA Localization Technology Based on LS and MUSIC ...

引用

8th International conference on Cyber Security and Information Engineering, ICCSIE 2023

作者： Hao, Fuzhong Liang, Lei Li, Nuannuan Mu, Linhai Zhi, Haiyan State Grid Henan Electric Power Company Zhengzhou450018 China Beijing Smartchip Microelectronics Technology Co. LTD Beijing100192 China State Grid Henan Electric Power Research Institute Zhengzhou450018 China

ISBN: (纸本)9798400708800

The estimation of incoming wave direction of Bluetooth 5.1 protocol provides a new way to realize high precision indoor positioning of mobile terminals. Aiming at the problems of low accuracy of real-Time Bluetooth Angle estimation and poor stability of continuous positioning caused by indoor multipath interference, a joint location algorithm of least squares and multiple signal classification was proposed. The positioning base station adopts rectangular array, which is divided into reference array and positioning array. While the positioning array collects the phase of incoming wave signal, the least squares algorithm estimates the phase of reference array, and then realizes the two-dimensional Angle estimation based on phase difference through multiple signal classification algorithm. The joint location algorithm realizes the time synchronization of incoming wave phase of rectangular array antenna and reduces the multipath error of signal acquisition. The simulation and experimental results verify the advanced theory of least square and multiple signal classification joint algorithm. The joint algorithm improves the positioning accuracy and stability in the indoor static and moving process, and has high application value. CCS CONCEPTS •Information systemsg1/4Information systems applicationsg1/4Mobile information processing systems © 2023 ACM.

关键词： Multiple signal classification

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NeuroSonic: An Innovative Neuroacoustic Therapy to Enhance Mental Wellness with EEG Brain signal

NeuroSonic: An Innovative Neuroacoustic Therapy to Enhance M...

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2024 IEEE Calcutta conference, CALCON 2024

作者： Paul, Trisha Das, Susmita Chowdhuri, Swati Chanda, Ankur Neogi, Biswarup Chaudhuri, Sheli Sinha Jadavpur University Electronics and Telecommunication Engineering Department Kolkata700032 India Narula Institute of Technology Department of Electronics and Computer Science Kolkata700109 India Electronics and Electrical Engineering Department Institute of Engineering and Management Kolkata700091 India Kolkata700091 India R&DJIS College of Engineering Kolkata741235 India

ISBN: (纸本)9798331516666

NeuroSonic' presents an innovative EEGbased music treatment system painstakingly designed to improve mental wellness. NeuroSonic is a program that uses state-of-the-art algorithms to evaluate brainwave data from the frontal and temporal lobes within a particular frequency band. Leveraging electroencephalography (EEG) data obtained from participants engaged in to solve mathematical problem statements. The research aims to elucidate the distinct patterns of neural activation across different brain lobes. Through meticulous statistical analysis of EEG signals, the underlying mechanisms governing brain activity before and after listening the healing sounds and these conditions are explored using EMOTIVE. The study employs advanced signal processing techniques and statistical analysis to discern temporal and spatial dynamics in neural responses. We have collected EEG data from 20 no. of subjects both male and female. ANOVA analysis is used for statistical representation and SVM algorithm is used for data modelling process. We got 85 percent accuracy in data modelling. The challenging job is the mapping of EEG data and integrating it into the proposed device. This method utilizes EEG data and frequency analysis to create customized sonic settings for Autism patients, enhancing their mental health and endurance through therapeutic auditory experiences. © 2024 IEEE.

关键词： mHealth

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Space Time Adaptive processing for High signal to Clutter Ratio Target's Detection Radar System

Space Time Adaptive Processing for High Signal to Clutter Ra...

引用

2022 International conference on Augmented Intelligence and Sustainable Systems, ICAISS 2022

作者： Pandey, Ananjay Hasan, Mahmud Raj, A.A.Bazil Defence Institute of Advanced Technology Radar System Laboratory Electronics Department Pune India

ISBN: (纸本)9781665489621

In this paper the various methods for clutter suppression are discussed, like SMI, DPCA and Matrix Manifold and reviewed MATLAB's study based on these algorithms. In the further section of this paper comparison between these algorithms based on simultaneous processing of clutter as well as Jammer can be seen based on MATLAB study. As we know In a radar system, transmitting antenna will transmit the RF signal after transmission of a radio frequency signal, the signal is received by the receiving antenna, which is composed of transmitted signal echo and several other undesired signals also. Among these signals, clutter signals as well as jammer signals may be present. The role of a jammer is to continuously transmit the wide spectrum of radio frequency signals towards radar so that the receiver section of radar gets random noise or false information or, in some cases, it may get saturated also. Hence, the received signal will be a weighted sum of target return echo, clutter and jammer signal. which makes it a 3-D signal. Suppression of clutter in non homogenous media is also a challenge. To separate the desired signal from other unwanted components, Space Time Adaptive processing techniques can be used. Simultaneous application of spatial as well as temporal filtering techniques can give better improvement in slow moving target detection by cancelling the clutter and jammer signal. In STAP, the signal is filtered in both angular as well as the Doppler domain by suppressing the clutter and jammer signals. © 2022 IEEE.

关键词： Space time adaptive processing

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Lightweight helmet detection algorithm based on improved YOLOv5 2

Lightweight helmet detection algorithm based on improved YOL...

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2nd International conference on advanced algorithms and signal Image processing, AASIP 2022

作者： Li, Jianning Zhang, Junzhao Zhang, Xinyu Wang, Shuai College of Electrical and Power Engineering Taiyuan University of Technology Shanxi Taiyuan030024 China Software Institute Nanjing University Jiangsu Nanjing210093 China Shanxi Electric Drive and Internet of Things Engineering Research Center Shanxi Taiyuan030024 China Shanxi Province 1331 Project-Smart City Based on Big Data Lighting Data Sharing and Public Service Engineering Technology Research Center Shanxi Taiyuan030024 China Shanxi Intelligent Digital Lighting Union Laboratory Shanxi Taiyuan030024 China Shanxi Intelligent Digital Cultural Tourism Industry Research Institute Shanxi Taiyuan030024 China

ISBN: (纸本)9781510660571

In the construction process, wearing safety helmet can effectively reduce the injury caused by falling objects and hard objects. In order to detect the wearing of safety helmet during the construction process, a lightweight safety helmet wearing detection algorithm YOLOv5-CS is proposed and applied to the embedded equipment at the construction site. The algorithm is based on the improvement of YOLOv5 target detection algorithm. The improved CAShuffle module is used to form the backbone feature extraction network, which reduces the size of the original algorithm and ensures the detection accuracy of the algorithm;DIoU as the loss function, which makes the algorithm more conducive to detecting small targets such as hard hats;modify dataset, add the dataset on the basis of the original dataset and mark the safety helmet and the anchor frame of the person separately, and judge whether the worker wears the safety helmet by analyzing positional relationship of the identified anchor frame, use the algorithm combining K-means and genetic algorithm to predict the anchor frame of the dataset, and use Mosaic algorithm to enhance the data. The results show that the parameter quantity of YOLOv5-CS algorithm is 2.4M, less than one third of YOLOv5;The average precision decreased by only 4.2%;640x640 pictures can be recognized at 31 frames per second on Jetson Nano, a embedded platform. © 2022 SPIE.

关键词： signal detection

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An Improved GDE Source Number Estimation Method Based on Kurtosis

An Improved GDE Source Number Estimation Method Based on Kur...

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advanced algorithms and Control Engineering (ICAACE), International conference on

作者： Jun Li Zeyu Wang Jun Nie Xun Ye Shengqiang Liu Ning Zhao University of Science and Technology of China Hefei China Institute of Advanced Technology of University of Science and Technology of China Hefei China

ISBN: (数字)9798331535087

ISBN: (纸本)9798331535094

In the field of signal processing, estimating the number of sources is extremely crucial. However, traditional methods like AIC and GDE have significant drawbacks. In high signal-to-noise ratio (SNR) conditions, the accuracy of the AIC method drops sharply due to the characteristics of its penalty function. For the GDE method, the uncertainty in the value of the adjustment factor D(L) leads to fluctuations in the results. To address these issues, this paper proposes a GDE method improved based on kurtosis. By analyzing the characteristic differences in kurtosis, a higher-order statistic, between sound signals and noise, a formula for D(L) that is dynamically related to the kurtosis of the collected signals is constructed. Its calculation involves operations such as eigenvalue decomposition of the covariance matrix, and the estimation is completed according to the Gerschgorin disk criterion. Experiments demonstrate that in different noise environments and scenarios, this method significantly outperforms traditional methods in terms of estimation accuracy, noise resistance, and stability. It shows particularly prominent advantages in high SNR real-world scenarios, providing a better means for estimating the number of sources.

关键词： Accuracy Uncertainty Noise Stability criteria Estimation signal processing algorithms White noise Kurtosis signal to noise ratio Testing

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