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6th International conference on Intelligent Computing and signal processing (ICSP)

作者： Shaohui Zhou Jinchao Zhao Yong Gan Yuefeng Wang College of Computer Science and Technology Zhengzhou University of Light Industry Zhengzhou China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

During the storage process, tobacco leaves are vulnerable to infestation by Lasioderma serricorne. To achieve precise detection of this pest within stored tobacco leaves and provide real-time updates on pest activity, we propose a detection system based on an improved YOLOv5 model. Initially, an open-source hardware system is established to capture images of the pests, which are then transmitted to a computer terminal via a Wi-Fi network. Random data augmentation techniques, including translation, rotation, and the addition of Gaussian noise, are applied to expand the training set of Lasioderma serricorne images. Subsequently, the BiFormer attention mechanism is integrated to enhance the model's accuracy in detecting small targets such as Lasioderma serricorne. By combining the improved YOLOv5 model with hardware facilities and the detection system, a comprehensive device is formed. the results demonstrate that the improved YOLOv5 network model achieves an accuracy rate of 93.26% and an average detection precision of 92.40% for Lasioderma serricorne. Compared to models such as YOLO v3, Retinanet, Faster R-CNN, the original YOLOv5, and SSD, the improved YOLOv5 model exhibits superior detection performance, with efficiency improvements of 2.76% and 2.46% over the existing YOLOv5 algorithm, respectively. the integration of the improved YOLOv5 model with hardware and the detection system into a comprehensive device fully harnesses the latest advancements in modern computer vision and artificial intelligence technologies. this device not only offers efficient object detection capabilities but also adapts well to various environments and scenarios, opening up a wide range of application possibilities. In this study, the device accurately identifies and counts Lasioderma serricorne, providing technical support for early warning and pest control in tobacco storage systems.

关键词： YOLO Training Adaptation models Accuracy Computational modeling signal processing algorithms signal processing Pest control Real-time systems Wireless fidelity

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Research on small Target Pedestrian Detection Algorithm Based on Improved YOLOv3 14th

Research on Small Target Pedestrian Detection Algorithm Base...

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14th International conference on Genetic and Evolutionary Computing, ICGEC 2021

作者： Liu, Shuaishi Geng, Yining Song, Yihu Yan, Wenyang Lian, Yufeng College of Electrical and Electronic Engineering Changchun University of Technology Changchun130000 China

ISBN: (纸本)9789811684296

Aiming at the problem that the target pedestrians’ environment in the intelligent driving system is complex and the detection accuracy is not high due to large size changes, the YOLOv3 algorithm is improved in this paper and the K-means clustering method to directly calculate the anchor frame size of the data set is used. Perform cluster analysis to reduce network training *** multi-scale fusion of shallow features and deep features improves the feature extraction effect of the skeleton network;the SE module is introduced to enhance the spatial channel after the multi-level feature fusion, which promotes the ability of pedestrian multi-scale information mining, and integrates the DIoU loss function Introducing the training process speeds up the model convergence and running *** model was trained with VOC2007, VOC2012 and Caltech datasets, and the Caltech pedestrian dataset was used to verify the effectiveness of the improved algorithm. the results show that the improved YOLOv3 algorithm for small-scale pedestrian targets in the intelligent driving system has improved detection accuracy. © 2022, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Cluster analysis

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Evaluating Predictive Business Process Monitoring Approaches on small Event Logs 14th

Evaluating Predictive Business Process Monitoring Approaches...

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14th International conference on the Quality of Information and Communications Technology (QUATIC)

作者： Kaeppel, Martin Jablonski, Stefan Schoenig, Stefan Univ Bayreuth Inst Comp Sci Bayreuth Germany Univ Regensburg Regensburg Germany

ISBN: (纸本)9783030853464;9783030853471

Predictive business process monitoring is concerned with the prediction how a running process instance will unfold up to its completion at runtime. Most of the proposed approaches rely on a wide number of machine learning techniques. In the last years numerous studies revealed that these methods can be successfully applied for different prediction targets. However, these techniques require a qualitatively and quantitatively sufficient dataset. Unfortunately, there are many situations in business process management where only a quantitatively insufficient dataset is available. the problem of insufficient data in the context of BPM is still neglected. Hence, none of the comparative studies investigates the performance of predictive business process monitoring techniques in environments with small datasets. In this paper an evaluation framework for comparing existing approaches with regard to their suitability for small datasets is developed and exemplarily applied to state-of-the-art approaches in next activity prediction.

关键词： Process mining Predictive business process monitoring small sample learning Process prediction

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Measurements on Extended Vertical Objects for Radar Field Probes 14

Measurements on Extended Vertical Objects for Radar Field Pr...

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14th European conference on Antennas and Propagation (EuCAP)

作者： Wei, P. S. P. Boeing Co Seattle WA USA

ISBN: (纸本)9788831299008

As a novel field probe concept, RCS measurements are reported on long rigid objects rotated within a small angular range about the broadside condition (called a glint). the rotation was maintained either in a horizontal (H) plane or in a vertical (V) plane containing the center of the quiet-zone (QZ). processing the RCS data by DFT yields a spectrum which is recognized as the field distribution along that object. Such spectrum compares extremely well to traditional field probes taken earlier by translating a sphere across the QZ in the H- or V-direction. Preliminary results at several S-band frequencies are presented and discussed.

关键词： RCS measurements large targets compact range field distribution

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Long-Time Coherent Integration Algorithm for Sea Surface Maneuvering small Target Based on Dynamic Programming 4

Long-Time Coherent Integration Algorithm for Sea Surface Man...

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4th IEEE International conference on Electronics Technology, ICET 2021

作者： Zhang, Yao Liu, Dunge Xia, Zhenghuan Zhang, Tao Zhao, Zhilong Guo, Yuhua Liu, Xin Yang, Yuqian Zhang, Kejia Shi, Huifeng Beijing Institute of Satellite Information Engineering State Key Laboratory of Space-Ground Integrated Information Technology Beijing China

ISBN: (纸本)9781728176734

Detection of sea surface maneuvering small target has long been faced with the problems of strong sea clutter background and low signal-clutter-noise ratio (SCNR), the long-time coherent integration algorithm can effectively improve the SCNR. A long-time coherent integration algorithm is proposed in this paper to process the echo signals of sea surface strongly maneuvering targets with both range and Doppler frequency migration. By using the idea of stage optimization, this algorithm can compensate the range and Doppler frequency migration at the same time, efficiently accumulate the target energy along the trajectory of the target, and effectively improve the SCNR of the target. In addition, this algorithm can also achieve the precise tracking of the target speed and position during the accumulation process, and is suitable for any maneuvering mode. the actual data processing and analysis show that this algorithm can realize the effective accumulation of maneuvering targets with low SCNR, and the accumulation gain is improved by more than 6dB compared with existing methods. © 2021 IEEE.

关键词： Dynamic programming

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Search for supersymmetric sleptons and charginos with the ATLAS detector

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JOURNAL OF INSTRUMENTATION 2023年第8期18卷 C08009页

作者： Ballabene, Eric Univ Bologna Dept Phys & Astron Augusto Righi Viale Berti Pichat 6-2 Bologna Italy Ist Nazl Fis Nucl Sez Bologna Viale Berti Pichat 6-2 Bologna Italy

A new search for the electroweak production of supersymmetric particles decaying into two leptons with missing transverse momentum is presented. Two simplified models are considered: direct pair production of sleptons decaying into the lightest neutralinos through leptons of the Standard Model (SM) and direct pair production of the lightest charginos decaying into the lightest neutralinos through bosons of the SM. the analysis targets phase space regions where the difference in mass between the slepton or the lightest chargino and the lightest neutralino is close to or below the mass of the boson. Such regions with compressed mass spectra have not been covered by any searches conducted so far due to the low cross-section of the supersymmetric signal. therefore, improved analysis strategies are crucial to separate the supersymmetric signal from the SM backgrounds. A search for an excess of same-flavour lepton pairs in opposite-sign lepton events is made in the direct slepton pair production analysis while a machine learning approach using boosted decision trees is exploited in the chargino pair production analysis and considering both the same-flavour and different-flavour channels. No significant excesses over the expected background are observed using proton-proton collisions data collected by the ATLAS experiment at root = 13 TeV and exclusion limits at 95% confidence level are set for each considered model. Exclusion limits are also set for selectrons and smuons separately and portions of the region excluded by the search of smuons pair production are expected to be compatible with the - 2 anomaly for small tan values.

关键词： Analysis and statistical methods data processing methods

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Dense Convolution Siamese Network for Hyperspectral Image Target Detection

Dense Convolution Siamese Network for Hyperspectral Image Ta...

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IEEE International conference on Information Communication and signal processing (ICICSP)

作者： Kun Shen Weixin Xie Haojin Tang Yanshan Li ATR National Key Laboratory of Defense Technology Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen China

Compared with grayscale and RGB images, hyperspectral image (HSI) can provide both spatial and spectral information of ground targets, which makes it possible to improve the efficiency and accuracy of target detection. therefore, the research of HSI target detection algorithms has attracted widespread concern in recent years. With the development of hardware devices and the arrival of big data era, deep learning algorithms have been successfully applied to image processing, text recognition and other fields. However, due to the complex gathering environment of HSI, it is so difficult to obtain a large number of labeled samples, which limits the application of deep learning algorithms in HSI target detection. therefore, a dense convolution Siamese network (DCSN) is proposed for HSI target detection, which improves the accuracy in the scenery of small-scale training samples. the main contributions of this paper include the following three points. First, we design a target sample generation method based on improved autoencoder to enhance target training data. then, a background selection method based on density estimation is presented, which can acquire typical background samples effectively. Finally, a spectral feature extraction method based on dense convolution is proposed to extract the more discriminative spectral features. the experimental results of HSI target detection on Muufl Gulfport and San Diego datasets indicate that our proposed DCSN is able to achieve superior performance than the existing target detectors.

关键词： Deep learning Training Convolution Text recognition signal processing algorithms Training data Object detection

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To Augment or Not to Augment? data Augmentation in User Identification Based on Motion Sensors 27th

To Augment or Not to Augment? Data Augmentation in User Iden...

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27th International conference on Neural Information processing

作者： Benegui, Cezara Ionescu, Radu Tudor Univ Bucharest 14 Acad Bucharest Romania

ISBN: (纸本)9783030638221;9783030638238

Nowadays, commonly-used authentication systems for mobile device users, e.g. password checking, face recognition or fingerprint scanning, are susceptible to various kinds of attacks. In order to prevent some of the possible attacks, these explicit authentication systems can be enhanced by considering a two-factor authentication scheme, in which the second factor is an implicit authentication system based on analyzing motion sensor data captured by accelerometers or gyroscopes. In order to avoid any additional burdens to the user, the registration process of the implicit authentication system must be performed quickly, i.e. the number of data samples collected from the user is typically small. In the context of designing a machine learning model for implicit user authentication based on motion signals, data augmentation can play an important role. In this paper, we study several data augmentation techniques in the quest of finding useful augmentation methods for motion sensor data. We propose a set of four research questions related to data augmentation in the context of few-shot user identification based on motion sensor signals. We conduct experiments on a benchmark data set, using two deep learning architectures, convolutional neural networks and Long Short-Term Memory networks, showing which and when data augmentation methods bring accuracy improvements. Interestingly, we find that data augmentation is not very helpful, most likely because the signal patterns useful to discriminate users are too sensitive to the transformations brought by certain data augmentation techniques. this result is somewhat contradictory to the common belief that data augmentation is expected to increase the accuracy of machine learning models.

关键词： data augmentation signal processing User authentication Motion sensors Deep neural networks

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Design and Implementation of Network Monitoring System Back End for 3T Regions with Parallel processing 14

Design and Implementation of Network Monitoring System Back ...

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14th International conference on Telecommunication Systems, Services, and Applications (TSSA)

作者： Pangestu, Dimas Aji Shalananda, Wervyan Edward, Ian Joseph Matheus Iskandar Bandung Inst Technol Sch Elect Engn & Informat Jl Ganesha 10 Bandung 40132 Indonesia

ISBN: (纸本)9781728175980

the increasing need for internet communication networks, various institutions and government agencies are demanded to be able to provide internet services in all regions in Indonesia, especially 3T regions. In providing this internet facility, we need a system that can monitor network devices that have been installed at various points so that the quality of the services provided can be maintained. the purpose of this final project is to design and implement a Network Monitoring System (NMS) that can monitor network devices, especially VSAT (Very small Aperture Terminal), and provide data in the form of uptime, traffic, ping, signal quality factor, and availability that can help in handling problems that occur on the network so that the performance of these devices can still meet the standards and service level agreement (SLA) that has been determined. Design and implementation methods are carried out with the stages of problem identification, identification of engineering requirements, determination of design alternatives, implementation, and product testing. the testing results show that the Network Monitoring System that was designed meets the Telecommunication Management Network standard of ITUT M.3400 and meets the design requirements that have been determined for systems that can monitor network devices. In addition, the testing results show that using multiprocessing as a parallel computation method can speed up program execution time 2 to 8 times compared to before using multiprocessing method.

关键词： network monitoring system VSAT uptime traffic signal quality factor availability SLA multiprocessing

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A Multi-Precision Floating-Point Multiplier Structure Applied to FPGA Embedded DSP 23

A Multi-Precision Floating-Point Multiplier Structure Applie...

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Proceedings of the 2023 6th International conference on Artificial Intelligence and Pattern Recognition

作者： Yuehang Li Zhihong Huang Gang Cai Rui Chen School of Communications and Information Engineering & School of Artificial Intelligence Xi?an University of Posts & Telecommunications China Ehiway Microelectronic Science and Technology China and Aerospace Information Research InstituteChinese Academy of Sciences China

ISBN: (纸本)9798400707674

Embedded floating-point DSP hardcore, as a floating-point arithmetic unit in FPGA, is widely used in the fields of image processing, signal processing, deep learning acceleration, etc., while the requirements for accuracy in different fields are *** order to support the computing needs of many fields in different accuracy, the mainstream embedded DSP currently supports a variety of accuracy floating-point or fixed-point number arithmetic; and the multiplier structure in the arithmetic unit mainly adopts a recursive multiplicer instruments stitching of multiple small wide multiple instruments,this structure supports multiplication operations with multiple accuracy floating-point or fixed-point numbers. However, there are defects in this structure, that is, the hardware resource sharing occupied by different accuracy data in the internal operation of the multiplier is low, thereby waste of hardware resources in chip resources. therefore, this article proposes a data segmentation/packaging method, designed a multi-precision multiplier structure (compact multi-precision multiplier) that improved on the basis of traditional dual-precision floating-point multiplier. Use the structure of high-precision floating-point multiplier to support multiple low-precision floating-point multiplication operations,It solves the problem that the hardware resources occupy too much. the experiment uses the SMIC 14nm standard CMOS process design; compares it through the traditional dual-precision floating-point multiplier, a separate floating-point multiplier, and a recursive multiplier. Compared with the recursive multiplier, the design area was reduced by 43.16%, the half-precision floating-point computing performance increased by 15.39%, the single-precision floating-point computing performance increased by 12.07%, and the dual-precision floating-point computing performance increased by 32.4%.

关键词： Booth Booth coding data segmentation Embedded DSP FPGA Multi-precision floating-point multiplier

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