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

作者： Wenbo Liu Tao Deng Fei Yan Southwest Jiaotong University Chengdu China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Intelligent vehicles need to provide rational driving strategies for assisted driving systems based on driving scenarios. Since pedestrians and vehicles are the main players in these scenarios, accurate detection and localization of pedestrians and vehicles are crucial for intelligent driving systems to make reliable decisions in dynamic environments. However, existing pedestrian and vehicle detection models often lack robustness under dynamic and complex traffic conditions, resulting in missed detections and false alarms, which pose significant safety risks. To address this problem, we categorize complex traffic scenarios into three typical challenges: long-distance, truncation, and occlusion, and focus on designing a novel enhancement stage to make the model more robust to these challenges. In this enhancement stage, inspired by human visual perception, we design a Visual Attention Module (VAM). This module can gather high-quality horizontal and vertical spatial features and efficiently interact between horizontal and vertical spatial features, enhancing the model’s perceptual ability by mimicking optic chiasm. Additionally, we use a Feature Reconstruction Module (FRM) to reduce redundant information in the feature maps and enhance the model’s inference ability. We conduct comprehensive experiments on the KITTI benchmark and Cityscapes dataset, and the experimental results demonstrate that our algorithm achieves state-of-the-art performance in various challenging scenarios.

关键词： Location awareness Visualization Pedestrians Signal processing algorithms Robustness Safety Vehicle dynamics Speech processing optical signal processing Visual perception

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algorithms, devices, and systems for optical information processing III / Bahram Javidi, Demetri Psaltis, chairs/editors;sponsored and published by SPIE--The International Society for optical Engin

Algorithms, devices, and systems for optical information pro...

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1999年

作者： Bahram Javidi Demetri Psaltis chairs/editors sponsored and published by SPIE--The International Society for optical Engineering.

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algorithms, devices, and systems for optical information processing : proceedings, 20-23 July 1998, San Diego, California / Bahram Javidi & Demetri Psaltis, Chairs/Editors;Sponsored and Published b

Algorithms, devices, and systems for optical information pro...

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1998年

作者： Bahram Javidi & Demetri Psaltis Chairs/Editors Sponsored and Published by SPIE-The international society for optical engineering.

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A Substation Safety Measure Ticket Generation Algorithm based on Neural Network and Inference Engine

A Substation Safety Measure Ticket Generation Algorithm base...

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Intelligent systems and Computational Networks (ICISCN), International conference on

作者： Yin Wu Huicai Zhao Xingfu Huang Liqiong Huang Yuyang Hu Guangxi Power Grid Power Dispatching and Control Center Nanning China Guangxi Power Grid Limited Liability Company Nanning Power Supply Bureau Nanning China Guangxi Power Grid Limited Liability Company Guilin Power Supply Bureau Guilin China

ISBN: (数字)9798331529246

ISBN: (纸本)9798331529253

Intelligent substations use fiber optic as the information transmission medium, transforming the interconnection relationship between secondary devices into fiber optic connections. The corresponding secondary circuits and hardware platforms are replaced with virtual circuits and software templates, resulting in a significant change in maintenance work methods and higher requirements for operators' maintenance work. This article proposes an intelligent substation safety measure ticket generation algorithm based on multi-scale feature convolutional neural network (MSF-CNN) and inference machine. Firstly, a neural network model suitable for safety ticket generation was designed and trained. Combining the structural characteristics of DenseNet, multi-scale feature extraction and logical relationship modeling were achieved through multi-layer convolution, concatenation, and pooling processing. The model uses hyperbolic tangent function as the activation function to improve the accuracy of regression prediction. Secondly, a custom word vector and equipment association modeling method based on SCD file parsing are proposed for the electricity proprietary terms and multi item logical relationships involved in the safety measures ticket text, in order to improve data expression accuracy and model understanding ability. In addition, based on the functional correlation and input-output interaction characteristics of substation equipment, a three-layer neural network-based inference engine was constructed to generate maintenance safety measures for primary and secondary equipment. The experimental results showed that the MSF-CNN model performed the best in accuracy, recall, and F1 score, with an accuracy of 92.5%, recall of 90.8%, and F1 score of 91.6%.

关键词： optical fibers Substations Accuracy Neural networks Training data Data models Inference algorithms Safety Maintenance Engines

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A survey on routing algorithm and router microarchitecture of three-dimensional Network-on-Chip

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Journal of systems Architecture 2025年 164卷

作者： Zhang, Yuan Jing, Zewei Yang, Qinghai Cheng, Nan Gu, Huaxi Kwak, Kyung Sup State Key Laboratory of ISN School of Telecommunication Engineering Xidian University Xi'an710071 China Guangzhou Institute of Technology Xidian University Guangzhou510555 China of Information Technology and Telecommunications Inha University Incheon22212 Korea Republic of

The continuous advancement of modern integrated circuits has facilitated the emergence of three-dimensional Networks-on-Chip (3D NoC), characterized by their direct vertical inter-layer electrical connections, which significantly enhance interconnect density. The performance and efficiency of 3D NoC architectures are jointly influenced by routing algorithms and router microarchitectures, which exhibit a symbiotic and complementary relationship. Routing algorithms are instrumental in determining the pathways for data packet transmission, profoundly influencing network latency, throughput, and reliability. Meanwhile, the router executes these algorithms, optimizing overall system efficiency through judicious resource allocation and effective data processing management. In this survey, we categorize routing algorithms according to various criteria, providing a detailed analysis of oblivious, adaptive, and hybrid oblivious-adaptive algorithms based on their degrees of adaptivity. Furthermore, we examine router microarchitectures, classifying them into buffered, bufferless, and hybrid buffered-bufferless designs, depending on whether buffering mechanisms are employed. This survey offers a comprehensive analysis of the co-evolution and co-design of routing algorithms and router microarchitectures, emphasizing that the alignment of an optimal routing algorithm with the appropriate microarchitecture is critical for better 3D NoC performance. © 2025 Elsevier B.V.

关键词： Data reduction

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algorithms, devices, and systems for optical information processing

Algorithms, Devices, and Systems for Optical Information Pro...

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algorithms, devices, and systems for optical information processing 1997

The proceedings contain 34 papers. The topics discussed include: ophthalmologic image normalization using optical correlation;distortion-invariant pattern recognition using composite Fourier plane nonlinear filtering;robust target recognition based on fractal analysis;real-time two-dimensional electronic image filtering and live TV restoration;how to optically implement N-dimensional pattern recognition;optimum distortion-invariant filtering algorithm for detecting maritime targets in overlapping and nonoverlapping background noise;identification of complex scattered signals with a fast real-time hybrid electro-optical correlator;and highly robust pose estimator based on synthetic estimation filters.

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Eye side and orientation detection of iris images using lightweight textural descriptors for embedded systems

Eye side and orientation detection of iris images using ligh...

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International Image processing, Applications and systems conference (IPAS)

作者： Chung Nguyen Tran Jordi Carrabina David Castells-Rufas Minh Son Nguyen Le-Anh Tran Nhan Cach Dang Departament de MiSE Universitat Autònoma de Barcelona Spain Dept. of Computer Engineering University of Information Technology Ho Chi Minh City Vietnam Dept. of Research and Development Mindintech Inc. Seoul South Korea IITEEE HCMC University of Transport Ho Chi Minh City Vietnam

ISBN: (数字)9798331506520

ISBN: (纸本)9798331506537

Iris recognition is a widely used biometric authentication technique due to its high accuracy and uniqueness. However, these systems are vulnerable to spoofing attacks, which can occur by rotating an iris image or an iris scanner during image acquisition. Additionally, correctly recognizing the eye side significantly reduces computational load and decreases the likelihood of false positives in biometric systems. This paper introduces a novel method for automatically detecting the correct left/right and upright/upside-down orientation of an iris image. The proposed method employs a lightweight feature extraction algorithm utilizing Local Binary Pattern (LBP) and Gray-Level Co-Occurrence Matrix (GLCM) to extract features from the iris image. A Support Vector Machine (SVM) classifier is then used to determine the eye side or orientation of the iris images. LBP captures the local texture details, whereas GLCM describes the statistical features of the iris images. By combining these textural features, the proposed method improves the ability to classify eye side or orientation. The efficient and precise texture descriptors allow for implementation on embedded systems, including IoT or mobile devices. Experimental results on benchmark datasets demonstrate that the proposed method outperforms existing baseline methods in both performance and speed.

关键词： Support vector machines Performance evaluation Embedded systems Feature extraction Biometric authentication Mobile handsets Computational efficiency Classification algorithms Security Iris recognition

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Smart Medical Box using Arduino

Smart Medical Box using Arduino

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International conference on ent Computing and Control systems (ICICCS)

作者： Sweadha. M M. Selvi Dept. of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai Tamil Nadu

ISBN: (数字)9798331512088

ISBN: (纸本)9798331512095

The Smart Medical Box is a sophisticated IoT-driven solution designed to enhance medication adherence by utilizing computer vision and machine learning. The system automates the identification and extraction of essential information from medication labels, ensuring precision in dosage reminders and reducing human error. It incorporates a high-resolution camera, an OCR engine, and an Arduino-based microcontroller to enable seamless image processing and real-time analysis. With an intuitive interface and GPS-enabled location services, users can efficiently manage their medication schedules while accessing nearby pharmacies when needed. This research focuses on designing and implementing a scalable and cost-effective system that improves medication compliance and minimizes health risks associated with missed or incorrect dosages. By integrating advanced image processing techniques and AI-driven recognition algorithms, the Smart Medical Box ensures high accuracy in identifying medications. Additionally, features such as automated alerts, real-time monitoring, and pharmacy locator tools enhance the system's usability and accessibility. This innovation is particularly beneficial for elderly individuals and patients with chronic conditions, offering a simplified and automated approach to medication tracking. Performance evaluations of the system indicate a significant improvement in medication adherence, a high recognition accuracy rate, and positive user feedback. Future enhancements, including AI-based OCR, voice assistance, and mobile application connectivity, are expected to further improve functionality and ease of use. This paper presents the conceptualization, development, and testing of the Smart Medical Box, highlighting its potential to revolutionize personal healthcare management by providing an intelligent, efficient, and user-friendly solution.

关键词： Accuracy Image recognition Microcontrollers optical character recognition Medical services Real-time systems Usability Older adults Biomedical imaging Global Positioning System

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Digital Twin Use Case in Telecommunications Transport Network

Digital Twin Use Case in Telecommunications Transport Networ...

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IEEE conference on Wireless Communications and Networking

作者： Ibrahim Fatih Mercimek Kemal Polat Muhammed Duran Yazar Network Architecture Department Turk Telekom Istanbul Türkiye Electrical and Electronics Engineering Department Bolu Abant Izzet Baysal University Bolu Türkiye

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

Digital Twin (DT) is a high-fidelity simulation technique that converts a real-world workplace into a virtual environment. information technology and the industrial industry are now deeply integrated and developing as a result of the advent of DT technology. The application of this technology to telecommunications has come to the forefront. In this study, artificial intelligence methods were applied for failure root cause analysis in transport systems adapted to digital twin technology used in telecommunication systems. Three different classification methods were used to analyze the obtained data. The Synthetic Minority Oversampling Technique (SMOTE) model was used to stabilize the data. The study includes the analysis of a data pool created by correlating the data received from the devices belonging to the fiber optic cable (Fiber), Dense Wavelength Division Multiplexing (DWDM) systems, and Internet Protocol Multi-Protocol Label Switching (IP-MPLS) layer, which constitute the transport layer of telecommunication systems. The use of DT terminology in telecommunication technologies is directly related to determining which use case to address, which domains, and which parameters to take in the existing network. For this purpose, the DT structure created by topologically associating DWDM technology and IP-MPLS technology, and then matching them at fault and alarm level, is used in root cause analysis prediction using artificial intelligence algorithms. As the output of the data pool; 3 basic error conditions “MPLS Flap”, “Short Term Interruption”, and “Long Term Interruption”, which cause interruptions on the user side, are discussed. Random Forest (RF), Naive Bayes (NB), and K-Nearest Neighbors (KNN) methods were used as artificial intelligence classification methods. When the results are analyzed, it is seen that the results of the Random Forest (RF) method are the most accurate prediction.

关键词： Radio frequency Root cause analysis optical fiber cables Nearest neighbor methods Wavelength division multiplexing Telecommunications Digital twins Classification algorithms Artificial intelligence Random forests

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Stereo-Correct Digital Magnification of the Physical World Using Video-Pass-Through Augmented Reality

Stereo-Correct Digital Magnification of the Physical World U...

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Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE conference on

作者： Jerald Thomas Mohammed Safayet Arefin Doug Bowman University of Wisconsin - Milwaukee Colorado State University Virginia Tech

ISBN: (数字)9798331514846

ISBN: (纸本)9798331525637

Video-pass-through (VPT) augmented reality (AR) enables greater field of view and fidelity compared to current optical-see-through AR technologies. However, the computational complexity of VPT AR has traditionally resulted in high latency, low resolution, and/or visual artifacts. Only recently have devices come on the market that successfully mitigate these drawbacks, such as the Varjo XR-3 and XR-4, the Apple Vision Pro, and the Meta Quest 3. We propose that low-latency VPT AR introduces several interesting 3D User Interface (3DUI) capabilities. In this position paper, we discuss one of these 3DUIs, namely stereo-correct digital magnification of the physical environment. Specifically, this paper presents a novel system for stereo-correct digital magnification of the physical environment using the Varjo XR-3 (but that can be generalized to other VPT AR systems). The digital magnification algorithm we propose enables stereoscopic magnification of physical objects in real time by utilizing the front-facing camera feeds of the VPT AR system, implemented entirely through software. In addition, we outline the challenges and limitations associated with the proposed system, discuss our current progress, and suggest potential future directions for the development of our proposed VPT AR digital magnification system.

关键词： Performance evaluation Visualization Three-dimensional displays Stereo image processing Software algorithms User interfaces Software Real-time systems Usability Augmented reality

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