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检索条件"任意字段=2023 3rd International Conference on Detection Technology and Intelligence System, DTIS 2023"

共 2101 条记录，以下是361-370 订阅

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Channel Estimation Based on Improved Compressed Sensing Algorithm with Reconfigurable intelligence Surface Assistance 3

Channel Estimation Based on Improved Compressed Sensing Algo...

引用

3rd international conference on Computer Science, Electronic Information Engineering and Intelligent Control technology, CEI 2023

作者： Chen, Mengmeng Liu, Hu Yang, Xinrui School of Railway Transportation Shanghai Institute of Technology Shanghai China

ISBN: (纸本)9798350372052

Aiming at the problem of cascade channel estimation for Reconfigurable Intelligent Surface (RIS) assisted wireless communication systems, an improved Compressive Sensing (CS) algorithm based on double-structure sparsity is proposed in this paper. Firstly, the double-structure sparsity characteristic of cascade channel in RIS assisted wireless communication system is studied. Then, aiming at the problem that base station (BS) and users cannot obtain channel sparsity before channel estimation, an improved compressed sensing algorithm is proposed. Simulation results show that the algorithm proposed in this paper can solve the problem of unknown channel sparsity. It is more practical than other compressed sensing algorithms without relying on complete prior information. © 2023 IEEE.

关键词： Compressed sensing

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Semi-Automated Image Annotation for Cannabis Seed Gender detection Model 3

Semi-Automated Image Annotation for Cannabis Seed Gender Det...

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3rd IEEE international conference on Software Engineering and Artificial intelligence, SEAI 2023

作者： Boonsri, Prachya Limpiyakorn, Yachai Chulalongkorn University Department of Computer Engineering Bangkok10330 Thailand

ISBN: (纸本)9798350337952

Many areas such as industrial, academic and medical have turned attention to the value and market opportunities that use cannabis as the new mixture. Due to the potential of its compounds, cannabis has become an economically viable plant. Many growers in Thailand are turning to cannabis as one of the yield crops and probably an alternative economically crop. The growers generally buy regular seeds for planting outdoor, resulting in the mix of growing up to male and female plants. The fact that only female cannabis plants are preferred as they provide valuable cannabinoid-rich flowers to harvest. Therefore, automated screening the gender of cannabis seeds upfront prior to plant could help lower waste and increase profitability. Agri-technology such as computer vision has played an important role in agriculture. Object detection models would facilitate sorting out female from male seeds. However, dataset annotation is resource consumption. This paper thus presents an approach of semi-automated image annotation as part of the YOLOv5 object detection model for gender screening of cannabis seeds. The preliminary result is promising. Compared to the model using manual annotation, the model using the proposed semi-automated annotation achieved comparable performance, and reduced half of the time spent on dataset annotation. © 2023 IEEE.

关键词： Object detection

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Assessment of the Charge Perturbation Effect of the Terahertz Pulse: Towards to the Space Charge Ellipsometry detection 3

Assessment of the Charge Perturbation Effect of the Terahert...

引用

3rd international conference on Power systems and Electrical technology, PSET 2024

作者： Gao, Haoyu Qi, Tianrun Ren, Hanwen Li, Qingmin Xiao, Tao Ma, Yiqun Ma, Yidan North China Electric Power University Beijing China

ISBN: (纸本)9798350353204

The space charge ellipsometry detection method offers a dependable technological approach for investigating the accumulation of insulating charge under intricate transient stresses. However, the potential of the THz pulse electric field to effectively disturb the space charge needs further assessment. This research analyzes the parameters that influence the intensity of the THz electric field and examines their respective roles according to the mechanism of THz pulse generation. In addition, the platform for assessing THz photoelectric field charge perturbation is devised and constructed, utilizing the PEA charge measurement method. The output voltage signal of the piezoelectric sensor under the THz photoelectric field is approximately equal to the output voltage signal under the electric pulse charge perturbation effect utilized in the PEA charge measurement system, which are in the millivolt range. © 2024 IEEE.

关键词： Electric fields

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Ground Fault detection for Transmission Lines Connected to Photovoltaic systems Using Inverters DC-Link Voltage 3

Ground Fault Detection for Transmission Lines Connected to P...

引用

3rd international conference on Computing and Information technology, ICCIT 2023

作者： Samkari, Husam S. University of Tabuk Department of Electrical Engineering Tabuk Saudi Arabia

ISBN: (纸本)9798350321487

This study proposes a ground fault detection method for transmission line systems connected to inverter-based resources (IBRs), such as electronically coupled wind turbines and solar photovoltaic (PV) systems. IBRs, typically, have an initial high-frequency transient response to power system faults with limited magnitudes of short circuit current, which is different from conventional synchronous generators. IBRs' fault contribution may impact distance protection by reducing the security or dependability of the element. Distance protection may misoperate by tripping for reverse faults or not tripping for forward faults when IBRs are the main source of fault current. The proposed ground fault detection method analyses dc voltage variation in inverters' dc-link to indicate fault location during single-line-to-ground (SLG) faults. The method is designed to aid distance protection to trip forward SLG faults faster and avoid tripping for reverse faults by communicating with the inverters through low-bandwidth communication channels. The PV system and the detection method are modeled and simulated using an electromagnetic transients program. © 2023 IEEE.

关键词： Electric power transmission

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Surface topography reconstruction method based on modulation of white light interference signal 3

Surface topography reconstruction method based on modulation...

引用

3rd international Computing Imaging conference, CITA 2023

作者： Chen, Weiwei Xiong, Yupeng Chen, Shanyong College of Intelligence Science and Technology National University of Defense Technology Changsha410073 China Laboratory of Science and Technology on Integrated Logistics Support National University of Defense Technology Changsha410073 China Hunan Key Laboratory of Ultra-Precision Machining Technology Changsha410073 China

ISBN: (纸本)9781510671409

In modern optical detection, the vertical resolution of three-dimensional(3-D) topography obtained by white light interferometer (WLI) can reach sub-nanometer level. Under the same detection environment, optical system and scanning sampling system, the quality of coherent peak extraction algorithm directly determines the measurement accuracy. After decomposing and analyzing the representation form of WLI signal, this paper proposes a surface topography reconstruction method based on the modulation function curve of interference signal for gaussian center positioning. Under the influence of typical error sources, the measurement accuracy of this method is simulated and analyzed. Finally, based on the method proposed in this paper, a comparative measurement experiment of 1.8µm standard step is carried out with ZYGO commercial interferometer. The simulation and experimental results show that the algorithm has good robustness and effectiveness. © 2023 SPIE.

关键词： Extraction

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Research on ITO Conductive Glass Chipping Defect detection Method based on Improved Skeleton Extraction 3

Research on ITO Conductive Glass Chipping Defect Detection M...

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3rd IEEE international conference on Information technology, Big Data and Artificial intelligence, ICIBA 2023

作者： Xiong, Jie Yin, Jian Liu, Jinsong Zhou, Qiujun Zhang, Kun College of Mechanical Engineering Tongling University TongLing China Key Laboratory of Construction Hydraulic Robots of Anhui Higher Education Institutes TongLing China New Copper-based Material Industry Generic Technology Research Center of Anhui Province TongLing China Anhui East China Photoelectric Technology Research Institute WuHu China Anhui Haoshi Optoelectronics Technology Co Ltd WuHu China

ISBN: (纸本)9781665490788

Aiming at the detection difficulties caused by edge bending, dirt, dust, etc. in the detection of chipping defects of ITO conductive glass based on machine vision, a chipping defect detection method based on improved skeleton extraction is proposed. First, pretreatment is performed prior to skeleton extraction, to remove the pseudo-skeleton caused by the influence of dirt, dust, and other noise. Secondly, according to the characteristics of chipping imaging, remove some algorithm links to improve algorithm execution efficiency;Finally, short straight line segmentation is unfolded after skeleton extraction, Based on the judgment of the number of short straight lines, the detection of chipping defects is realized. Experiments show that the improved algorithm has high efficiency and accuracy for the chipping detection of ITO conductive glass, and has high practical value. © 2023 IEEE.

关键词： Defects

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Multilingual Models for Sentiment and Abusive Language detection for Dravidian Languages 3

Multilingual Models for Sentiment and Abusive Language Detec...

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3rd Workshop on Language technology for Equality, Diversity and Inclusion, LTEDI 2023

作者： Anand Kumar, M. Department of Information Technology National Institute of Technology Surathkal Karnataka India

ISBN: (纸本)9789544520847

This work delves into the realm of abusive comment detection and sentiment analysis within code-mixed content, focusing specifically on Dravidian languages. The languages covered include Tulu, and Tamil. For this investigation, TFIDF-based Long Short-Term Memory (LSTM) and Hierarchical Attention Networks (HAN) are employed as the analytical tools. Interestingly, the research highlights the prevalence of traditional TF-IDF techniques over Hierarchical Attention models in both sentiment analysis and the identification of abusive language across the diverse linguistic landscape encompassing Tulu and Tamil. Of note is the Tulu sentiment analysis system, which demonstrates remarkable prowess in handling Positive and Neutral sentiments. In contrast, the sentiment analysis system tailored for Tamil exhibits comparatively lower performance levels. This discrepancy underscores the critical need for well-balanced datasets and intensified research endeavors to enhance the accuracy of sentiment analysis, particularly in the context of the Tamil language. Shifting focus to abusive language detection, the TF-IDF-LSTM models consistently outperform the Hierarchical Attention models. Intriguingly, the mixed models exhibit particular strength in classifying categories like "Homophobia" and "Xenophobia." This intriguing outcome accentuates the value of incorporating both code-mixed and original script data, presenting novel avenues for advancing social media analysis research in diverse linguistic scenarios involving the Dravidian languages. © 2023 LTEDI 2023 - 3rd Workshop on Language technology for Equality, Diversity and Inclusion, associated with the 14th international conference on Recent Advances in Natural Language Processing, RANLP 2023 - Proceedings. All rights reserved.

关键词： Sentiment analysis

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Deep Learning Based Real Time Fall detection Model 3

Deep Learning Based Real Time Fall Detection Model

引用

3rd international conference on Emerging Techniques in Computational intelligence, ICETCI 2023

作者： Sarma, H Aravind Jose, Jijo Mar Baselios College of Engineering and Technology Department of Electronics and Communication Trivandrum India

ISBN: (纸本)9798350300604

Health professionals are enormously utilising the advantages of most advanced technologies, leading to a scalable development in the field of health care. There has been a paradigm shift from manual monitoring towards more accurate virtual monitoring with a high accuracy rate. The world is very much concerned about taking care of old people. One of the worst things that can happen to older individuals is a fall. The creation of fall detection systems is urgently needed due to the aging population's rapid growth. With the development of technology, fall detection and rescue systems are able to provide quick emergency assistance to victims of accidental falls, thereby reducing the number of fatalities by detection of fall and providing adequate care. Here, we propose a model for real-Time fall detection that uses deep convolutional neural networks. An automated fall detection model is essential for elderly care, since it offers a real time monitoring and fall detection whereas manual fall detection and immediate attention depends on timely availability of many factors. A real time monitoring system coupled with Deep learning techniques can accomplish this task. For fall detection, many deep learning networks can be utilized. Here, we propose an efficient model for real-Time fall detection that uses deep convolutional neural networks and torch tensors. The system will recognize Fall and Non Fall from a set of real time input videos and respond according to scenario. We tried a hardware demonstration of an Automated Fall detection system in an Up Extreme Series single board computer with LSTM neural network model. © 2023 IEEE.

关键词： Fall detection

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Data Access Loss detection Method for data platforms-LDLD Model 3

Data Access Loss Detection Method for data platforms-LDLD Mo...

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3rd international conference on Frontiers of Electronics, Information and Computation Technologies, ICFEICT 2023

作者： Yang, Yadan Wang, Tianzuo Information Engineering University School of Cyberspace Security PLA Strategic Support Force Zhengzhou China

ISBN: (纸本)9798350302356

As the significantly acceleration of database and cloud computing technology, data centers have become increasingly integral to vital businesses in various industries, including government departments and enterprise institutions. Data quality issues are magnified in such circumstances. However, due to an extensive amount of data access and the intricate cross-domain environment, there are inevitable data loss problems in the access process. From the perspective of improving the observability of the whole data flow, this paper proposes a log-based data access loss detection (LDLD) model and constructs a prototype system. The experimental results in the actual system show that the LDLD model can effectively detect packet loss during data access and accurately locate the fault location. This study can provide key technical support for solving the data quality problems of data centers. © 2023 IEEE.

关键词： Packet loss

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Automatic Chest X Ray Pathology detection using Convolutional Neural Network 3

Automatic Chest X Ray Pathology Detection using Convolutiona...

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3rd international conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Hemalatha, T. Barve, Animesh Sivakumar, T.K. Computer Technologies SRM Institute of Science and Technology Kattankulathur Chennai India

ISBN: (纸本)9798350343632

This research study presents an automated Chest X-ray Pathology detection system employing Convolutional Neural Networks (CNNs) and transfer learning. Here, the primary research objective is to develop a robust medical diagnosis system for chest Xray images, capable of distinguishing among 14 distinct pathologies commonly found in these images, including lung infections, tumors, fractures, and cardiovascular conditions. This study utilizes the Keras framework and a pre-trained DenseNet CNN model for enabling efficient and accurate classification. This study involves comprehensive data preparation, transfer learning with DenseNet, addressing class imbalance, and model evaluation. The proposed system demonstrates promising results and potential for enabling significant improvements in medical diagnostics. © 2023 IEEE.

关键词： CNN modeling prediction X-Ray

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