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检索条件"主题词=Signal Processing Algorithms"

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Presenting a Method for Gluing Error Detection Using Image processing

Presenting a Method for Gluing Error Detection Using Image P...

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International Conference of signal processing and Intelligent Systems (ICSPIS)

作者： Moein Shishebor Vali Derhami Masoud Khouri Computer Engineering Department Yazd University Yazd Iran

ISBN: (数字)9798331532543

ISBN: (纸本)9798331532550

The application of artificial intelligence and image processing for automatic fault detection in industrial settings holds substantial significance. However, image processing systems encounter challenges in achieving accurate automatic detection, including variable lighting conditions, low image quality, and the complexity of observed objects. This study specifically addresses the detection of gluing errors in automotive parts. An improved template matching algorithm is employed to identify boundary errors. The proposed method incorporates SIFT (Scale-Invariant Feature Transform) for feature extraction, allowing for the identification of key local features in images regardless of changes in scale, rotation, or lighting conditions. To address variations in scale and alignment, affine transformations are employed to standardize the images, ensuring consistent dimensions and orientations. After this preprocessing step, brute-force matching techniques are utilized to accurately match the extracted features from the modified images with a target reference, refining the output and enhancing the detection accuracy of improperly glued areas. Results from executing the algorithm on input images demonstrate the high performance of the proposed method in gluing error detection.

关键词： Accuracy Refining signal processing algorithms Lighting Transforms signal processing Feature extraction Reliability Standards Automotive engineering

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Thickness Measurement of Alloy Steel Carburizing Layer Based on Laser Ultrasonic

Thickness Measurement of Alloy Steel Carburizing Layer Based...

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Advanced Information, Mechanical Engineering, Robotics and Automation (AIMERA), IEEE International Conference on

作者： Xing Mao Dong Xu Shaotong Zhang Xiaocheng Wang Quan Yang Ruixiao Wang Wei Sun Rengfei Yu Institute of Engineering Technology University of Science and Technology Beijing Beijing China School of Mechanical Engineering and Automation Northeastern University Shenyang China Capital Engineering & Research Incorporation Limited Beijing China Hot Rolling Workshop Angang Steel Company Limited Anshan China

ISBN: (数字)9798350343335

ISBN: (纸本)9798350343342

Carburizing is one of the most widely used chemical heat treatment processes in the machinery manufacturing industry. The surface hardness, wear resistance and flexural fatigue strength of the workpiece after carburization is greatly improved. The thickness of the carburized layer is one of the main technical indicators to measure the quality of carburized parts. However, at present, the carburized shaft carburized layer thickness inspection is generally a contact method. In this paper, the thickness of the carburized layer of alloy steel was detected using Laser Ultrasonic (LU) non-destructive testing technology. First of all, using simulation signals to verify the effectiveness of sparse decomposition reconstruction and wavelet threshold denoising algorithm, and then the use of sparse decomposition and reconstruction combined with wavelet threshold denoising algorithm on the experimental LU signal denoising to extract the weak signal, obtained carburized layer thickness of alloy steel, accuracy of test results up to more than 95%. This study provides theoretical and data support for the development and application of on-line inspection equipment for carburized layers.

关键词： Ultrasonic variables measurement Noise reduction signal processing algorithms Measurement by laser beam Inspection Acoustics Time measurement Steel Thickness measurement Testing

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When Artificial Intelligence meets Navarasas - Facial Expression Classification in Kathakali Using DSFD and CNN

When Artificial Intelligence meets Navarasas - Facial Expres...

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IEEE International Conference on signal processing, Informatics, Communication and Energy Systems (SPICES)

作者： Ganesh Neelakanta Iyer Nattapong Saengarunvong Minh Hien Le Department of Computer Science School of Computing National University of Singapore Singapore Department of Computer Engineering Faculty of Engineering King Mongkut’s University of Technology Thonburi Bangkok Thailand Department of Computer and Data Sciences Case School of Engineering Case Western Reserve University Cleveland Ohio USA

ISBN: (数字)9798350376135

ISBN: (纸本)9798350376142

Kathakali, an ancient art form that dates back to the 17th century, is renowned for its intricate hand gestures, dance movements, musical accompaniment, elaborate costumes, and makeup. Mastering such an art form is a challenge even for the most dedicated enthusiasts, given its unconventional methods of expression. However, with current advanced technology, we can use this to aid the learning of unfamiliar subjects by classifying factors to help the new learners. In this paper, we focus on classifying one aspect of the play, which is the expressions on the actor’s face given a picture using computer vision methods. To achieve the final model, we use a combination of Dual Shot Face Detector (DSFD) and Convolution Neural Network (CNN) and finally tuning up the epochs of the training process. With our dataset, the proposed model reached an accuracy of 93% among nine classes. This project hopes to introduce Kathakali to a wider audience and facilitate the learning process of this art form.

关键词： Training Accuracy Art Computational modeling signal processing algorithms Detectors Data models Faces Tuning Testing

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The Industrial Internet Security Situation Assessment Method Based on AHP-CRITIC Hybrid Weighting

The Industrial Internet Security Situation Assessment Method...

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signal processing and Intelligent Computing (SPIC), International Conference on

作者： Ling Yang Shuheng Xu Lixin Hou Yaodong Tao Shenyang LiGong University School of Information Science and Engineering Shenyang China Beijing DualPi Intelligent Security Technology Shenyang China College of Information and Technology Jilin Agricultural University Changchun China School of Computer and Information Technology Beijing Jiaotong University Beijing China

ISBN: (数字)9798350368888

ISBN: (纸本)9798350368895

The assessment index system for industrial Internet network security relies too heavily on expert knowledge and overlooks the impact of objective factors on situation assessment. This paper addresses this issue by focusing on the characteristics of industrial networks, specifically the impact of asset vulnerabilities and alarm events on network situation. A comprehensive weighted hierarchical industrial Internet situation assessment method is proposed. The final comprehensive weight is obtained using the least square method, combined with the supervisor weight calculated by the analytic hierarchy process and the objective weight calculated by the CRITIC method. Finally, a network security experiment center is used to carry out situation assessment, and the evaluation value is calculated. Experimental results demonstrate that this method provides a more objective and accurate approach to situation assessment.

关键词： Knowledge engineering Internet security signal processing algorithms Focusing Analytic hierarchy process Simulated annealing Network security signal processing Indexes Least mean squares methods

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Fast Dependent Quantization Using Trellis Pruning, Forward Context Adaptation and Vectorization

Fast Dependent Quantization Using Trellis Pruning, Forward C...

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European signal processing Conference (EUSIPCO)

作者： Adam Wieckowski Christian Stoffers Heiko Schwarz Benjamin Bross Detlev Marpe Video Communication and Applications Deptartment Fraunhofer HHI Berlin Germany

ISBN: (数字)9789464593617

ISBN: (纸本)9798331519773

Dependent quantization (DQ) is one of the key coding tools in the Versatile Video Coding (VVC) standard. DQ employs two scalar quantizers, with the per-coefficient quantizer selection being governed by a parity-driven 4-state state machine. As the design is normatively enforced, usage of DQ requires a rate-distortion optimized quantization (RDOQ) with a per coefficient decision and state update, e.g. a trellisbased quantization, as initially proposed for the VVC reference software (VTM). Due to its inherent dependencies, including VVCs context selection based on previously encoded coefficient values, and fairly broad search range, the trellis quantization is computationally highly complex. Reducing the complexity of this algorithm is crucial for practical VVC encoders. In this paper we propose a fast dependent quantization trellis search improving the initial design by: trellis pruning of improbable branches, forward adaptive context propagation, and finally a vectorized implementation. The proposed approach, implemented in the open and optimized VVenC encoder, reduces quantization runtime by 37%, allowing an overall 15% encoder speedup in medium preset with no impact on compression performance, in all-intra coding conditions. In random-access conditions, an 9% overall encoder speedup is achieved.

关键词： Video coding Quantization (signal) Runtime Software algorithms signal processing algorithms Encoding Optimization Standards Testing Software development management

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Clustering algorithms Study for Audio Insertion Detection

Clustering Algorithms Study for Audio Insertion Detection

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Information Technology and Nanotechnology (ITNT), International Conference on

作者： Ilia Moiseev Aleksey Maksimov Samara National Research University Samara Russia

ISBN: (数字)9798350372939

ISBN: (纸本)9798350372946

In this paper, we reflect on a problem of audio editing detection. We consider a certain type of editing - the insertion of falsified fragments into an audio recording. To detect such insertions, we propose an algorithm based on audio background noise clustering. For the proposed algorithm, various methods for background noise preprocessing, various neural feature extractors and various clustering algorithms are examined. Based on the experimental research, we select a combination of a preprocessing method, a feature extraction model and a clustering algorithm that gives the best clustering metrics. The combination of ResNet feature extractor and agglomerative clustering yielded the best results.

关键词： Measurement signal processing algorithms Clustering algorithms Feature extraction Audio recording Background noise Data mining

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The Performance Enhancement of Image Segmentation Technique based on VLSI Technology

The Performance Enhancement of Image Segmentation Technique ...

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Innovative Trends in Information Technology (ICITIIT), International Conference on

作者： Anandakumar Haldorai R Babitha Lincy M Suriya Minu Balakrishnan P Mithun Centre for Future Networks and Digital Twin Sri Eshwar College of Engineering Coimbatore TamilNadu India

ISBN: (数字)9798350386813

ISBN: (纸本)9798350386820

Image segmentation is essential when processing images for medical purposes. The weak image contrast and scattered organ or tissue borders make it challenging to segment medical images. Due to significant developments in engineering technology, many diagnostic procedures in medicine are now automated and use image processing techniques. VLSI design’s purpose in medical image segmentation is to offer quick and effective hardware solutions for identifying anatomical structure boundaries in a variety of medical pictures. Very large-scale integration, or VLSI, is a technique for building integrated circuits by fusing millions of transistors onto a single chip. The performance, speed, accuracy, and power consumption of image segmentation algorithms, which are frequently computationally demanding and complicated, can be improved through VLSI design. Thus, in this study, the Xilinx System Generator (XSG) and FPGA are used to implement the segmentation of brain tumors on hardware. Due to extensive parallelism and pipelining, it beats conventional programmable digital signal processorsand even Personal Computer with coprocessors in terms of performance, design time, and cost. The complexity of architectural design is significantly reduced when using XSG for medical image processing applications. Additionally, the potential of hardware co-simulation is offered.

关键词： Image segmentation Costs signal processing algorithms Very large scale integration Hardware Transistors Medical diagnostic imaging

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Optimization of Passivity-Based Controller for a Hybrid Vehicle Power Source using the Gray Wolf Algorithm

Optimization of Passivity-Based Controller for a Hybrid Vehi...

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International Conference on Image and signal processing and their Applications (ISPA)

作者： Said Bedda Okba Kraa Messaoud Mohammedi Djallal Eddine Zabia Ilyes Tegani Mohamed Kamel Benbraika Energy Systems Modeling Laboratory Mohamed Khider University Biskra Algeria LI3CUB Laboratory Mohamed Khider University Biskra Algeria Department of Science and Technology University Center of Barika Barika Algeria University of El-Oued El-Oued Algeria

ISBN: (数字)9798350309249

ISBN: (纸本)9798350309256

This paper introduces an enhanced approach for the control of hybrid sources, specifically fuel cells and batteries, within a hybrid electric vehicle. The proposed enhancement involves integrating the Gray Wolf Optimization algorithm with the passive-based control technique. The primary aim of this research is to enhance the operational characteristics of the studied system that is governed by the passivity-based control approach. This enhancement is achieved by optimizing the damping matrix parameter using the Gray Wolf Optimization algorithm. It is noteworthy that prior studies utilizing this technique did not address its impact, considering it a stochastic value ranging from 0 to 1. The central focus remains on proficiently and effectively managing the energy exchange between the two sources. Through Simulink-Matlab simulations, the outcomes underscore the influence of the damping matrix parameter on the overall dynamic performance of the system. Moreover, these results emphasize its pivotal role in achieving tracking precision and system robustness. This research constitutes a significant advancement in the realm of sophisticated control methodologies for hybrid power sources. Furthermore, it lays the groundwork for future investigations and the potential implementation of supplementary energy management strategies based on this innovative technique.

关键词： Damping Heuristic algorithms signal processing algorithms Fuel cells Hybrid power systems Batteries Hybrid electric vehicles

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Neural-Network-based Pitch-lag Estimation in Long-term Linear Prediction

Neural-Network-based Pitch-lag Estimation in Long-term Linea...

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International Carpathian Control Conference (ICCC)

作者： Ales Jandera Tomas Skovranek BERG Faculty Technical University of Kosice Kosice Slovakia

ISBN: (数字)9798350350708

ISBN: (纸本)9798350350715

This paper presents a novel method for neural-network-based pitch-lag estimation implemented within the framework of linear prediction. In comparison to the standard autocorrelation pitch-lag estimation technique, the proposed approach exploits the capability of AI algorithm, namely a re-current neural network, to enhance the accuracy of long-term linear prediction by means of efficient pitch-lag identification. The proposed approach not only showcases the potential of AI to outperform traditional methods in signal processing but also opens new ways for refining the analysis of pitch-related phenomena in diverse applications.

关键词： Adaptation models Recurrent neural networks Accuracy Estimation signal processing algorithms signal processing Autocorrelation

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Implementation of the Optical Lock through Visible Light Communication using AES

Implementation of the Optical Lock through Visible Light Com...

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Advances in signal processing, Power, Communication, and Computing (ASPCC), IEEE International Conference on

作者： K.P. Swain Sumant Kumar Mohapatra Puspanjali Mallik R. K. Dash Rakesh Kumar Lenka Department of ETC Trident Academy of Technology Bhubaneswar India Dept. of CSE Shailabala Women’s College Cuttack India Dept. of Electrical Electronics and Communication Engineering Galgotia University Dept. of Computer Science Central University of Odisha Sunabeda Koraput

ISBN: (数字)9798350355093

ISBN: (纸本)9798350355109

This study presents the development and implementation of a novel optical lock using visible light communication (VLC), leveraging a custom-built mobile application and flash LED for secure information transmission. The system utilizes an Android application with a user-friendly interface to input and encrypt messages using the AES-128 bit algorithm and Base64 encoding. The encrypted message is transmitted via a smartphone’s flash LED as an OOK signal, received by a specially designed PCB composed of a photodiode and a servo motor. At the heart of the receiving mechanism is a Raspberry Pi, which is responsible for decrypting the message and executing a comparison check with a pre-stored message to determine system unlocking. This innovative approach combines the convenience of mobile technology with advanced encryption, offering a robust solution in optical locking systems.

关键词： Heart signal processing algorithms Information processing Light emitting diodes Mobile applications Encryption Photodiodes Optical signal processing Servomotors Visible light communication

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