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A Mining Conveyor Belt Tear Detection Method based on Improved STDC 9

A Mining Conveyor Belt Tear Detection Method based on Improv...

引用

9th International symposium on Computer and Information Processing technology, ISCIPT 2024

作者： Wang, Zhen Li, Xiaoming Taiyuan University of Science and Technology Department of Computer Science and Technology Taiyuan China

ISBN: (纸本)9798350388404

real-time and accurate detection of conveyor belt tears is a key issue in industrial applications, and this problem is still not well solved. In this paper, we propose an improved STDC network to enhance the performance of tear detection. Firstly, the STDC module in the backbone network is reorganized to enhance the feature extraction capability of the network. Secondly, the object filtering module is designed to capture the inter-channel dependencies while discarding useless information to reduce feature redundancy. Lastly, in the feature fusion stage, the fusion of high-level semantic information and low-level spatial information is strengthened by focusing on the channel and spatial features at the same time, which optimizes the output of the network. Experimental results show that detection performance of our method in complex environments is significantly improved with an FPS of 39.5 and an mIoU of 91.39%. Compared with other algorithms, our method achieves a better balance between segmentation speed and accuracy. © 2024 ieee.

关键词： Semantic Segmentation

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HgPCN: A Heterogeneous Architecture for E2E embedded Point Cloud Inference 57

HgPCN: A Heterogeneous Architecture for E2E Embedded Point C...

引用

57th Annual ieee/ACM International symposium on Microarchitecture, MICRO 2024

作者： Gao, Yiming Jiang, Chao Piard, Wesley Chen, Xiangru Patel, Bhavesh Lam, Herman University of Florida United States Dell EMC United States

ISBN: (纸本)9798350350579

Point cloud is an important type of geometric data structure for many embedded applications such as autonomous driving and augmented reality. Current Point Cloud Networks (PCNs) have proven to achieve great success in using inference to perform point cloud analysis, including object part segmentation, shape classification, and so on. However, point cloud applications on the computing edge require more than just the inference step. They require an end-to-end (E2E) processing of the point cloud workloads: pre-processing of raw data, input preparation, and inference to perform point cloud analysis. Current PCN approaches to support end-to-end processing of point cloud workload cannot meet the real-time latency requirement on the edge, i.e., the ability of the AI service to keep up with the speed of raw data generation by 3D sensors. Latency for end-to-end processing of the point cloud workloads stems from two reasons: memory-intensive down-sampling in the pre-processing phase and the data structuring step for input preparation in the inference phase. In this paper, we present HgPCN, an end-to-end heterogeneous architecture for real-time embedded point cloud applications. In HgPCN, we introduce two novel methodologies based on spatial indexing to address the two identified bottlenecks. In the Pre-processing Engine of HgPCN, an Octree-Indexed-Sampling method is used to optimize the memory-intensive down-sampling bottleneck of the pre-processing phase. In the Inference Engine, HgPCN extends a commercial DLA with a customized Data Structuring Unit which is based on a Voxel-Expanded Gathering method to fundamentally reduce the workload of the data structuring step in the inference phase. The initial prototype of HgPCN has been implemented on an Intel PAC (Xeon+FPGA) platform. Four commonly available point cloud datasets were used for comparison, running on three baseline devices: Intel Xeon W-2255, Nvidia Xavier NX Jetson GPU, and Nvidia 4060ti GPU. These point cloud datase

关键词： Edge computing

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Kalman Filter: A Crucial Step Towards the Development of NavIC 10

Kalman Filter: A Crucial Step Towards the Development of Nav...

引用

10th ieee International symposium on Smart Electronic Systems, iSES 2024

作者： Sharma, Avinash Dutta, Abhishek Deb, Sujay National Institute of Technology Durgapur Dept. Of Electronics and Communication Engineering West Bengal Durgapur India Indraprastha Institute of Information Technology Delhi Dept. Of Electronics and Communication Engineering Delhi New Delhi India

ISBN: (纸本)9798331533229

Navigation with Indian Constellation (NavIC) is an autonomous satellite system consisting of seven constellations, with three in geostationary orbit and four in geosynchronous orbit. Achieving precise positioning and velocity estimations under noisy conditions is crucial for applications such as vehicle guidance, disaster management, and transportation improvement. We propose a novel implementation of a Kalman Filter for processing NavIC satellite measurements, optimizing position, velocity, and timing estimations. The innovation in this filter design lies in its efficient noise reduction and high accuracy in estimations. Our design achieves a power consumption of 0.103 Wand an area of 84303.850 μ m2. To further enhance the design, we aim to incorporate clock gating and power gating techniques, reducing overall power consumption and making it highly suitable for low-power, real-time navigation applications. © 2024 ieee.

关键词： Kalman filters

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embedded Flexible Shape Cable for Marine Exploit applications 22

Embedded Flexible Shape Cable for Marine Exploit Application...

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22nd International Conference on Optical Communications and Networks, ICOCN 2024

作者： Tan, Tao Chai, Quan Tian, Ye Shi, Shan Zhang, Jianzhong Harbin Engineering University Key Lab of In-Fiber Integrated Optics Ministry of Education Harbin150001 China Deep Sea Engineering Technology Research Center Harbin Engineering University Harbin150001 China

ISBN: (纸本)9798350367652

An embedded flexible shape cable has been first proposed and the verification of real-time shape measurement has been achieved. It is produced by sequentially preparing shape sensing units, shape sensing optical cables, and optoelectronic composite cables. Temperature has little effect on shape reconstruction over a long period of time, and the end stability is less than 0.012m. real-time shape measurement is achieved in both vertical and horizontal directions within a range of 4.5 m. The curvature measurement accuracy is 0.05 m1 and the shape reconstruction errors are 3.0% and 1.7%, respectively. The flexible shape cables can be used for shape monitoring in areas such as power transmission cables between islands and flexible pipeline cables for offshore oil and gas resource extraction, improving the safety of marine resource development. © 2024 ieee.

关键词： Marine applications

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2024 ieee symposium on VLSI technology and Circuits, VLSI technology and Circuits 2024

2024 IEEE Symposium on VLSI Technology and Circuits, VLSI Te...

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2024 ieee symposium on VLSI technology and Circuits, VLSI technology and Circuits 2024

ISBN: (纸本)9798350361469

The proceedings contain 249 papers. The topics discussed include: on the reliability of high-performance dual gate (DG) W-doped In2O3 FET;a 12-bit 10GS/s time-interleaved SAR ADC with even/odd channel-correlated absolute error-based over-Nyquist timing-skew calibration in 5nm FinFET;14nm FinFET node embedded MRAM technology for automotive non-volatile RAM applications with endurance over 1E12-cycles;an intra-body-power-transfer system energized by an electromagnetic energy harvester for powering wearable sensor nodes;first demonstration of high retention energy barriers and 2 ns switching, using magnetic ordered-alloy-based STT MRAM devices;cell to core-periphery overlap (C2O) based on BCAT for next generation DRAM;and a 25.4–27.5GHz ping-pong charge-sharing locking PLL achieving 42fs jitter with implicit reference frequency doubling.

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Lightweight Hand-Waving Action Recognition Using Reservoir Computing in a Cafeteria Environment

Lightweight Hand-Waving Action Recognition Using Reservoir C...

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2025 ieee/SICE International symposium on System Integration, SII 2025

作者： Isomoto, Kosei Fumoto, Soma Kobayashi, Ryohei Tanaka, Yuichiro Tamukoh, Hakaru University of Kitakyushu Faculty of Environmental Engineering 2-4 Hibikino Wakamatsu Kitakyushu808-0135 Japan Kyushu Institute of Technology Graduate School of Life Science and Systems Engineering 1-1 Hibikino Wakamatsu Kitakyushu808-0196 Japan Kyushu Institute of Technology Research Center for Neuromorphic AI Hardware 2-4 Hibikino Wakamatsu Kitakyushu808-0196 Japan

ISBN: (纸本)9798331531614

Owing to the global labor shortage and increasing need for operational efficiency, the adoption of service robots is advancing rapidly. These robots must recognize human action to understand human intention and respond appropriately based on that understanding. The action recognition systems embedded in robots need to be lightweight to operate efficiently with limited computational resources. Reservoir computing (RC) is one of the solutions for lightweight action recognition systems. Yamaguchi et al. proposed an RC-based hand-waving recognition system;however, the system cannot process multiple persons simultaneously and works only when one person is in the image. Therefore, this study proposes a lightweight hand-waving recognition system that integrates OpenPose, StrongSORT, and RC to work in complex environments with multiple individuals. Experimental results demonstrated the effectiveness of the proposed system in processing multiple people simultaneously in a crowded environment and accurately recognizing hand-waving actions with 90.75% accuracy. We also confirmed that the proposed system can process data at 24-26 FPS. We demonstrated that the proposed system can perform real-time processing. In addition, the robot with the proposed system recognized hand-waving actions in the "Restaurant"task of RoboCup@Home 2024 and obtained the second-place score. © 2025 ieee.

关键词： real time systems

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Understanding the Effects of a real-time Motion Capture System with Voice Feedback for Tennis Toss Training

Understanding the Effects of a Real-time Motion Capture Syst...

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2023 ieee International symposium on Medical Measurements and applications, MeMeA 2023

作者： Dhinesh, R. Preejith, S.P. Sivaprakasam, Mohanasankar Indian Institute of Technology Madras Department of Electrical Engineering Chennai India Iit Madras Healthcare Technology Innovation Center Chennai India

ISBN: (纸本)9781665493840

Skill learning in sports for beginners requires the attention of a trainer to achieve consistency and repeatability of actions by developing suitable muscle memory. The effectiveness of training may be compromised due to the skewed number of trainers and players, leaving the potential of determined and able individuals untapped. The proposed solution addresses this problem through a technology solution to aid training by customized monitoring of specific actions and providing suggestions for corrections in real-time. A wearable system consisting of wireless inertial sensor devices measures anatomic angles for repetitive motions during practice associated with skill learning. Correctness is determined in real-time by comparing the angles measured for actions with those of the trainer recommended actions. It is then evaluated by a voice feedback mechanism contained in the system and suggestions for incorporating action refinements are delivered. A short-term study involving beginner level tennis players was conducted to validate the effectiveness of the proposed solution. The system measured angles during the tennis serve tossing action and provided suggestions for hand positioning to develop consistent toss. real-time recommendations were given through the voice feedback mechanism, and its effects on players are quantified through statistical metrics. Analysis indicates 8 out of 13 players showed significant improvement in serving upon introduction of the system. On-the-field measurements and prompt feedback for corrections based on recommendations customized for each player show immense potential in accelerating skill perfection through assisted training. © 2023 ieee.

关键词： Tennis

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MULTI-GRAINED GLOBAL-LOCAL SEMANTIC FEATURE FUSION FOR FEW SHOT REMOTE SENSING SCENE CLASSIFICATION

MULTI-GRAINED GLOBAL-LOCAL SEMANTIC FEATURE FUSION FOR FEW S...

引用

ieee International Geoscience and Remote Sensing symposium (IGARSS)

作者： Liu, Yuqing Zhang, Tong Zhuang, Yin Wang, Guanqun Chen, He Beijing Inst Technol Beijing Key Lab Embedded Real Time Informat Proc Beijing 100081 Peoples R China

ISBN: (纸本)9798350320107

Few-shot remote sensing scene classification aims to classify unseen scenes by using only a few labeled samples. Hence, how to set up a more effective feature description according to a few labeled samples, becomes an important issue. In this paper, in view of more complicated remote sensing scenes containing several hierarchical and coupled spatial relations (e.g., internal and external spatial contexts), which severely hinder the feature extraction under few-shot learning scenarios, a multi-grained global-local semantic feature fusion (MGGL-SFF) method is proposed for few-shot remote sensing scene classification, which can better combine the global discriminative spatial semantic features with local transferable fragment features to set a powerful prototype representation up for few shot learning. Finally, experiments are carried out on defined few-shot remote sensing scene classification benchmark, and results proved the proposed MGGL-SFF can achieve a new state-of-the-art performance.

关键词： Few-shot learning remote sensing multi-grained scene classification global-local semantic feature fusion

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Ethical and Legal Implications to Data Collection in Virtual and Augmented reality

Ethical and Legal Implications to Data Collection in Virtual...

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2025 ieee symposium on Trustworthy, Explainable and Responsible Computational Intelligence, CITREx Companion 2025

作者： Karimov, Ayaz Ismayilzada, Aytaj Saarela, Mirka University of Jyväskylä Faculty of Information Technology Jyväskylä Finland

ISBN: (纸本)9798331519728

As immersive technologies such as Virtual reality (VR) and Augmented reality (AR) become increasingly integrated into various sectors, the ethical and regulatory challenges surrounding data collection in these environments are rapidly evolving. The complexity of VR/AR systems, which gather vast amounts of sensitive data, from biometric information to real-time user behavior, presents unique concerns regarding privacy, consent, and accountability. This paper explores the ethical implications of data collection in VR/AR environments by emphasizing the need for responsible and transparent practices. The paper discusses the adequacy of existing legal instruments in promoting user trust while ensuring compliance with ethical principles, highlighting areas where regulatory measures fall short. Additionally, the paper considers the role of explainable and responsible computational intelligence in enhancing accountability and mitigating risks in VR/AR applications. © 2025 ieee.

关键词： Ethical technology

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Water Quality Evaluation using Machine Learning 9

Water Quality Evaluation using Machine Learning

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9th International Conference on Communication and Electronics Systems, ICCES 2024

作者： Pongiannan, R.K. Sivakumar, Akash Kohli, Shivain Poornima, P.U. Lourde Jame, S. Pemila, M. Srm Institute of Science and Technology Department of Computing Technologies Kattankulathur India Srm Institute of Science and Technology Dept. of Electrical and Electronics Engg Kattankulathur India

ISBN: (纸本)9798350377972

Maintaining the water quality is vital for environmental sustainability,public health, and effective resource management. This research study outlines the development and deployment of a real-time water quality monitoring system., highlighting the essential parameters like pH., turbidity,and hardness. Machine learning algorithms,such as Random Forest(RF),K-Nearest Neighbor (KNN),and Artificial Neural Networks (ANN) are utilized to improve prediction accuracy and enable real-time water quality assessment. The water quality managements system has two parts namely the embedded hardware unit with sensor modules, and a machine learning models offers a scalable,cost-effective solution for real-time water monitoring,significantly improving the detection of contamination and enabling efficient water management across various applications. © 2024 ieee.

关键词： Resource allocation

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