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Research on simulation of human brain neural network and signal processing technology 5

Research on simulation of human brain neural network and sig...

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5th International conference on Signal processing and Computer Science, SPCS 2024

作者： Wang, Haochen Xuteli College Beijing Institute of Technology Beijing China

ISBN: (数字)9781510686731

ISBN: (纸本)9781510686724

With the cross development of computational neuroscience and artificial intelligence, research on human brain neural network simulation and signal processing technology has become a hot topic of common concern in both academia and industry. This study used a multi-level and multi-scale computational model and high-precision algorithm to simulate the dynamic behavior of human brain neural networks, exploring the complex interactions between neurons and their impact on information processing capabilities. Real time dynamic simulation of billions of neurons was achieved on a simulation platform using ultra large-scale integrated circuit chips, simulating signal processing patterns similar to those of the human brain. By using an improved backpropagation algorithm to decode and reconstruct neural signals, the efficiency of the algorithm and the accuracy of signal processing have been improved. On this basis, combined with experimental data obtained from functional magnetic resonance imaging, the similarities and differences between neural network simulation results and actual human brain activity were compared and analyzed, revealing the potential connection between cognitive function and brain network activity patterns. This study not only achieved new breakthroughs in simulation technology and signal processing algorithms, but also provided a new quantitative tool and theoretical support for related neuroscience research, which is of great significance for the development of brain computer interfaces and intelligent information processing systems. In addition, the study also delved into the balance between ensuring model complexity and processing efficiency, as well as the challenges and opportunities brought by interdisciplinary collaboration in the field of neuroscience. Through cross validation and error analysis of simulation experiments, the effectiveness of the model and the accuracy of prediction results were ensured. Based on this, feasible suggestions for opt

关键词： Magnetic resonance imaging

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Fusion of Sparse Direct Method and Feature-based Approach in Stereo Point-Line SLAM Algorithm

Fusion of Sparse Direct Method and Feature-based Approach in...

引用

2024 International conference on Mechatronics and Intelligent Control, ICMIC 2024

作者： Wang, Hao Xu, Zhen Leng, Kuang China Nanhu Academy of Electronics and Information Technology Zhejiang Jiaxing China School of Electronic Engineering and Computer Science University of Science and Technology of China Anhui Hefei China School of Management University of Science and Technology of China Anhui Hefei China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

The development of autonomous driving and augmented reality has led to increased demands for accuracy and speed in visual SLAM. Traditional feature-based visual SLAM performs real-time image analysis with high complexity and computation requirements, necessitating devices with exceptionally high arithmetic power. This poses challenges for deployment on low-power devices. Additionally, relying solely on photometric errors makes the system too sensitive to the environment. To tackle these issues, our algorithm integrates the feature-based method and the sparse direct method. We employ the sparse joint method for pose estimation in the tracking thread, considering both accuracy and speed. In case of tracking failure, we extract feature point lines for tracking. Furthermore,to enhance system robustness in low-texture environments and fuse point-line features, we employ adaptive weighted extraction of point-line features, considering computational resources. Our experimental results, based on public datasets, demonstrate that this algorithm achieves faster operation speeds in simple environments and higher accuracy compared to other SLAM algorithms in complex environments and fast camera movement scenes. © 2025 SPIE.

关键词： Stereo image processing

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Robust signal phase tracking in the gnss space-time array processing anti-interference receiver 6

Robust signal phase tracking in the gnss space-time array pr...

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6th International conference on Geoscience and Remote Sensing Mapping, GRSM 2024

作者： Xie, Yuchen Ni, Shaojie Ma, Ming Xiao, Wei Lei, Chen College of Electronic Science National University of Defense Technology Changsha China Key Laboratory of Satellite Navigation Technology Changsha China

ISBN: (纸本)9781510688018

Electromagnetic interference is one of the most serious threats to satellite navigation receivers, and the most effective countermeasures in the existing research is the space-time array processing (STAP) anti-interference technology. However, the traditional STAP will cause the signal signal phase to deviate, resulting in a decrease in phase tracking accuracy, or even serious consequences such as receiver loop loss. There are three bottleneck problem for the STAP bias correction, including the delay uncertainty in anti-interference filters, the non-ideal nature of the analog devices, and the unclearness of signal direction. Here, we propose a method for modifying the GNSS antenna array receiver’s signal phase deviation. Compared with the traditional algorithms, the proposed algorithm is implemented in a simple way and requires no a priori information. Simulation and 2 types of real data test results show that the proposed algorithm can effectively suppress the signal phase deviation caused by the STAP, and the residual error after the algorithm processing is less than 8°, which improves the receiver's signal phase tracking performance. © 2025 SPIE.

关键词： Antenna arrays

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Differential Protection for Distribution Grids Based on Dual Compressed Sensing Theory

Differential Protection for Distribution Grids Based on Dual...

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2024 International conference Optoelectronic information and optical Engineering, OIOE 2024

作者： Duan, Yahui Wu, Tonghua Chen, Wei Dai, Wei Cao, Yuhan Cao, Wenjun School of China EU Institute for Clean and Renewable Energy Huazhong University of Science and Technology Wuhan430074 China The State Key Laboratory of Technology and Equipment for Defense against Power System Operational Risks Nari Technology Co. Ltd. Jiangsu211106 China The State Key Laboratory of Advanced Electromagnetic Technology Huazhong University of Science and Technology Wuhan430074 China State Grid Hebei Electronic Power Research Institute Hebei250002 China State Grid Shandong Electronic Power Research Institute Shandong050011 China

ISBN: (数字)9781510688209

ISBN: (纸本)9781510688193

With the increasing integration of distributed renewable energy sources into distribution networks, the characteristics of fault currents in distribution networks have undergone significant changes. Traditional three-stage current protection is no longer sufficient to meet the protection requirements. In theory, a differential protection scheme can better fulfill the requirements of rapid and accurate fault detection and clearance in distribution networks. Differential protection relies on real-time communication for information exchange between devices, and many researchers have incorporated wireless networks such as 5G into distribution network differential protection. Given the exponential growth of data in distribution networks and the security considerations of wireless communication like 5G, this paper proposes a secure protection technique for distribution network differential protection based on dual compressed sensing theory. This technique employs two compressed sensing schemes to compress the data before transmission, reducing the amount of data transferred while enhancing security. Subsequently, secure determinations are made based on the data at both ends processed through the compressed sensing algorithm, ensuring the security of communication in distribution network differential protection while achieving the same level of protection performance as traditional differential protection schemes. © 2025 SPIE.

关键词： Compressed sensing Data transmission Matrices Data communications Wireless communications Network security Reconstruction algorithms Computer security Signal processing Signal to noise ratio

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A small target detection method based on different scales for unmanned aerial vehicles 3

A small target detection method based on different scales fo...

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3rd International conference on Electrical, Electronics, and information Engineering, EEIE 2024

作者： Qi, Xiuyuan Wang, Zheng Liu, Zherong Wei, Haojie Hao, Shuang Zhai, Yufei Liang, Qing Liu, Ye University of Electronic Science and Technology of China Chengdu China AVIC Chengdu Aircraft Design & Research Institute Chengdu China

ISBN: (纸本)9781510688179

With the continuous iteration and development of computer vision technology, intelligent applications and devices centered around this technology are gradually playing an increasingly important role in human daily life and military operations. Among these, technologies based on object recognition and detection are widely applied in fields such as robotics, drones, and aircraft combat. These areas require precise localization information provided by object detection technology to achieve functions like navigation or attack. However, due to the characteristics of the targets being detected, their scale changes according to their distance, resulting in significant scale variations in images for the same target. Timely detection of distant targets is crucial for aircraft control and early warning, making small target recognition a key factor limiting the widespread application of recognition algorithms. To address this issue, this paper processes the original images based on color space level, global level, and pixel level, proposing a small target recognition method for RGB images. This method involves separately processing different color spaces of the RGB image, followed by information fusion, analysis of the entire image and local regions, and pixel-level filtering in local areas. Experimental results demonstrate that our algorithm can accurately recognize targets of varying sizes and observation angles. © The Authors.

关键词： information fusion

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International conference on optical information processing

International Conference on Optical Information Processing

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International conference on optical information processing

ISBN: (纸本)9780819413109

The proceedings contain 142 papers. The topics discussed include: optical neural networks based on photorefractive beam fanning;photorefractive fiber storage, switching, interconnects, and the technological challenges;present capabilities in the use of optical information processing devices in the supercomputer architecture;new space-integrating acousto-optic correlator operating mode: linear filtering and forming of video-signals;parallel optoelectronic systems for computing and communications;optical commutation based on AO effects in Ti-diffused waveguides in LINBO3;chemically enhanced bacteriorhodopsin thin film spatial light modulator;integrated magnetooptic Bragg cell device modules for information processing;acoustooptoelectronical devises for processing of spread spectrum sygnals;integrated optical multichannel acousto-electro-optic device;and wideband (20MHz-160MHz) acoustooptical standing wave modulator for fluorometry and mode synchronization.

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Secure encryption system based on quantum access network 4

Secure encryption system based on quantum access network

引用

4th International Computational Imaging conference, CITA 2024

作者： Liu, Yuchao Wang, Tao Xu, Yuehan Zeng, Guihua State Key Laboratory of Advanced Optical Communication Systems and Networks Center of Quantum Sensing and Information Processing Shanghai Jiao Tong University Shanghai200240 China Shanghai Research Center for Quantum Sciences Shanghai201315 China Hefei National Laboratory CAS Center for Excellence in Quantum Information and Quantum Physics Hefei230026 China

ISBN: (纸本)9781510688834

Quantum secure communication technology, grounded in the principles of quantum mechanics, has revolutionized traditional cryptographic methods, which predominantly rely on mathematical algorithms and logical transformations. Quantum key distribution (QKD) facilitates the secure sharing of symmetric keys between legitimate parties, ensuring the integrity and confidentiality of information in communication channels. Among various QKD schemes, continuous variable quantum key distribution (CV-QKD) has emerged as a viable alternative to the more established discrete variable quantum key distribution (DV-QKD). CV-QKD boasts several advantages, including straightforward deployment, reduced operational costs, and stable signal quality, positioning it as a significant component of the quantum communication *** noise stream cipher (QNSC) represents a technique that employs redundant data streams to encrypt plaintext. Notably, QNSC shares structural similarities with the optical path used in quantum key distribution, allowing for compatibility with existing QKD infrastructure. Furthermore, the keys generated through quantum key distribution ensure absolute security, enabling them to substitute the data streams produced by pseudo-random sequences traditionally used in classical encryption schemes. This substitution enhances the overall security framework of the quantum noise stream encryption *** quantum access network (QAN) extends quantum key distribution capabilities from point-to-point connections to point-to-multipoint configurations, thereby becoming an essential component of contemporary network architectures. By interlinking multiple end users with a network backbone, quantum access networks can seamlessly integrate with quantum key distribution protocols. This integration offers a cost-effective and scalable solution for user access to the *** experimental verifications have demonstrated the viability of downstream access networks,

关键词： Quantum noise

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Vehicle Registration Plate Recognition Using YoloV8 and IOT 1

Vehicle Registration Plate Recognition Using YoloV8 and IOT

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1st International conference on AIML-Applications for Engineering and Technology, ICAET 2025

作者： Nadaf, Juber Kadam, Amol Jadhav, Pramod Kadam, Prasad Patil, Vinod Gaikwad, Milind College of Engineering Department of Computer Pune India College of Engineering Department of CSBS Pune India College of Engineering Department of E & TC Pune India College of Engineering Department of Information Technology Pune India

ISBN: (纸本)9798350355611

Number Plate recognition or the vehicle License Plate recognition is an interesting topic of research in smart cities which utilizes Image processing techniques. Since the number of cars is rising at an exponential rate, automated systems are supposed to store vehicle data for a variety of applications. In this intended algorithm, an efficient technique has been identified for recognition of different vehicle number registration plates. Through this technique, we can easily deal with problems like low light, irregular font number plates, wrong angles. We use the method of optical Character Recognition to identify characters that are extracted from the registration plate. Even though this project works efficiently for common use cases, it has its own drawbacks and limitations even though we are not using deep learning or any other machine learning algorithms. One of the important steps in vehicle plate recognition is the character recognition which is a technique to obtain individual text characters. YOLOv8 (You Only Look Once), and Darknet- 53 are the methods that is used to extract the features of the data. In this model, the input data is the image of the vehicle that is captured from the camera sensors or cell phones and later cropped to display only the registration plate. We undergo data-pre-processing to improve the quality or the pixels of image on the number plate. Testing is done using two different models one is the model which is obtained with more pre-processing data and the other obtained without any pre-processing data. We evaluate two datasets of number plate images: one with no interference and one where the colour intensity of the image has been decreased to test, the accuracy of the model © 2025 IEEE.

关键词： Deep learning

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Extracting Vitals from ICU Monitor Images: An Insight from Analysis of 10K Patient Data 27th

Extracting Vitals from ICU Monitor Images: An Insight from A...

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27th International conference on Pattern Recognition, ICPR 2024

作者： Rampuria, Akshat Khare, Kushagra Soni, Ayush Dogra, Debi Prosad School of Electrical and Computer Sciences Indian Institute of Technology Bhubaneswar Bhubaneswar752050 India

ISBN: (纸本)9783031781971

In intensive care units (ICUs), continuous monitoring of patient vitals is crucial for timely interventions and optimal outcomes. While traditional methods rely on direct observation by healthcare professionals, technological advancements have led to a growing interest in image-based monitoring systems, particularly utilizing closed-circuit television (CCTV) cameras within ICU environments. However, integrating such systems poses challenges, notably in extracting vital information from monitor images efficiently. Current approaches, including manual interpretation and specialized algorithms, are often laborious and error-prone. In response, this paper presents a robust pipeline for automatic extraction of patient vitals from ICU monitor images. Our approach involves automatic detection and segmentation of monitor screens, followed by extraction of relevant vital signs. By enhancing existing ICU environments with this technology, we aim to improve patient care and resource utilization. Our contributions include a powerful pre-processing pipeline, a comprehensive study of optical character recognition (OCR) frameworks, and a geometry-based heuristic implemented in kornia for vital sign detection. Through this work, we lay the groundwork for innovative solutions that can revolutionize patient monitoring in ICU settings. The method has been tested on a large dataset comprises with 10K ICU monitor images. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： optical character recognition

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Device-aware optical Adversarial Attack for a Portable Projector-camera System

Device-aware Optical Adversarial Attack for a Portable Proje...

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International conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Ning Jiang Yanhong Liu Dingheng Zeng Yue Feng Weihong Deng Ying Li School of Software & Microelectronics Peking University Beijing China Mashang Consumer Finance Co. Ltd. China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Deep-learning-based face recognition (FR) systems are susceptible to adversarial examples in both digital and physical domains. Physical attacks present a greater threat to deployed systems as adversaries can easily access the input channel, allowing them to provide malicious inputs to impersonate a victim. This paper addresses the limitations of existing projector-camera-based adversarial light attacks in practical FR setups. By incorporating device-aware adaptations into the digital attack algorithm, such as resolution-aware and color-aware adjustments, we mitigate the degradation from digital to physical domains. Experimental validation showcases the efficacy of our proposed algorithm against real and spoof adversaries, achieving high physical similarity scores in FR models and state-of-the-art commercial systems. On average, there is only a 14% reduction in scores from digital to physical attacks, with high attack success rate in both white- and black-box scenarios.

关键词： Integrated optics optical losses Heuristic algorithms Signal processing algorithms Speech recognition Radiometry optical signal processing Speech processing optical devices Optimization

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