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共 20484 条记录，以下是381-390 订阅

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Sustainable Solar Powered Bluetooth Enabled Smart Home Automation System Using internet-of-Things

Sustainable Solar Powered Bluetooth Enabled Smart Home Autom...

引用

2024 ieee international conference on Communication, Computing and signal Processing, IICCCS 2024

作者： Sharma, Jiya Sharma, Sachin Graphic Era Deemed to be University Department of Computer Science and Engineering Uttarakhand Dehradun India Graphic Era Deemed to be University Graphic Era Hill University Department of Computer Science and Engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350390759

People have always strived hard since long in order to develop a technology that eases their workload. The Home automation technology is a crucial example of such an innovation that humans have developed in order to simplify their tasks. It deals with creating a network between all the devices in the home, from LED lights and fans to even doors and more. Automating these tasks ensure that they happen simultaneously one after the other. In addition to that when we want to seek more control of things, the concept of internet of Things come into play. IoT will involve integrating these automated systems with a connectivity layer and then transmitting the data across various devices and interfaces. In this paper, Bluetooth is used for the connectivity purpose. Wireless connectivity will allow the user to remotely access all the devices, which opens numerous possibilities. Furthermore, this paper promotes energy conservation as the system will automatically adjust the device operations according to the external environmental conditions. Moreover, the entire system is solar powered adding a sustainable and eco-friendly touch to the paper. © 2024 ieee.

关键词： Smart homes

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Adaptive Dynamic Programming-based Feature Tracking Control for image Disturbances Visual Servoing Manipulators 9

Adaptive Dynamic Programming-Based Feature Tracking Control ...

引用

9th international conference on Control Science and systems Engineering, ICCSSE 2023

作者： Ren, Xiaolin Yan, Haoyu Ma, Bing Changchun University of Technology Department of Control Science and Engineering Changchun China

ISBN: (纸本)9798350339055

Aiming at the problem of feature point interference and noise in visual servoing (VS) control, an image feature tracking control method based on adaptive dynamic programming (ADP) is proposed. The output signal of the image sensor is used as the feedback signal of the VS manipulators system for closed-loop control. While the adaptive state observer is used to estimate the image disturbances in the VS model of the manipulator, and the cost function is improved according to the observed disturbance values. On the basis of ADP technology, a critic neural network (NN) was constructed to derive the Hamilton-Jacobi-Bellman (HJB) equation. According to Lyapunov theory, it is proved that the visual servoing manipulators system is asymptotically stable. Finally, numerical simulations are given to verify the effectiveness of the algorithm. © 2023 ieee.

关键词： Manipulators

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image Processing based on Inter-frame Color Feature Matching for Visible Light Positioning 2

Image Processing Based on Inter-frame Color Feature Matching...

引用

2nd international conference on signal Processing and Intelligent Computing, SPIC 2024

作者： Yu, Baozhu Liu, Xiangyu Chen, Yaoheng Guo, Lei Bao, Jianbo Sun, Jiandong Shenyang Ligong University School of Information Science and Engineering Shenyang China Southern University of Science and Technology Department of Computer Science and Engineering Shenzhen China Chongqing University of Posts and Telecommunications School of Communication and Information Engineering Chongqing China Nari Group Corporation State Grid Electric Power Research Institute Nanjing China

ISBN: (纸本)9798350368888

The indoor imaging visible light positioning (VLP) technology based on the image sensor (IS) utilizes existing indoor lighting infrastructure to provide high-precision indoor positioning services. However, due to the high complexity of traditional image processing algorithms, existing VLP systems are unable to provide real-time positioning services. In response to the above issue, we propose an image processing mechanism based on the inter-frame color feature matching method, which includes the equidistant sampling processing, low complexity decoding algorithm, and color feature matching-based LED region of interest (ROI) determination method. The results show that the system average positioning delay is 80.2ms, indicating better system real-time performance. © 2024 ieee.

关键词： Color image processing

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A Comparative Study of image Enhancement Algorithms for Abdomen CT images 2

A Comparative Study of Image Enhancement Algorithms for Abdo...

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2nd ieee international conference on Interdisciplinary Approaches in technology and Management for Social Innovation, IATMSI 2024

作者： Kaur, Harinder Kaur, Navjot Neeru, Nirvair Punjabi University Patiala Department of Computer Science and Engineering Patiala India

ISBN: (纸本)9798350360523

image enhancement techniques play a vital role in improving the visual quality and diagnostic value of Computed Tomography (CT) images. As medical imaging continues to be a cornerstone of diagnosis and treatment planning, advancements in image enhancement algorithms have become essential to aid medical professionals in accurately interpreting CT scans. This research paper presents a comprehensive review and comparative analysis of various image enhancement techniques applied to medical images, with a focus on abdomen CT imaging. The study categorizes these algorithms into histogram-based, transformation-based, and deep learning-based methods, assessing their respective strengths and limitations. The research employs a meticulous comparative analysis, considering metrics such as Peak signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), Average Mean Brightness Error (AMBE), Entropy, and Structural Similarity Index (SSIM) to evaluate the performance of these techniques. We conclude with the implications of the study's results, paving the way for informed decision-making when selecting enhancement techniques. © 2024 ieee.

关键词： image enhancement

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Indoor Human Detection based on Convolutional Neural Network and image-based Processing 6

Indoor Human Detection Based on Convolutional Neural Network...

引用

6th international conference on Natural Language Processing (ICNLP)

作者： Yang, Junhua Bai, Guodong Lu, Jingyu Xian Univ Posts & Telecommun Sch Elect Engn Xian Peoples R China

ISBN: (纸本)9798350349122;9798350349115

Indoor human detection technology is a critical component in the fields of indoor security and smart furniture. The current technology, which is based on Wi-Fi Channel State Information (CSI), relies solely on a single CSI amplitude information, resulting in a less stable human body detection system. To overcome this limitation, this study introduces a novel method, CSI-image Processing (CSI-IP), which combines the lightweight convolutional neural network SqueezeNET with the traditional signal processing technology, and integrates CSI amplitude information and phase information. The method involves processing the original phase information and amplitude information using linear transform and wavelet transform, respectively, and constructing CSI amplitude image and phase image. These images are then fused using the Laplace pyramid fusion algorithm, and a convolutional neural network is used to classify and learn the fused image to achieve human body detection. Experimental results in four different environments (laboratory, laboratory corridor, library, and library corridor) show that the detection rate of the algorithm is 0.9264, 0.9416, 0.9068, 0.9464, respectively, which is significantly higher than that of traditional algorithms under the same conditions, demonstrating the effectiveness and stability of the method.

关键词： CNN CSI human detection image processing

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Robust image watermarking using Tikhonov regularized image reconstruction technique 2

Robust Image watermarking using Tikhonov regularized image r...

引用

2nd ieee international conference on Interdisciplinary Approaches in technology and Management for Social Innovation, IATMSI 2024

作者： Rajput, Shayam Singh Rai, Deepak Arya, K.V. National Institute of Technology Patna Department of Cse Patna India Bennett University School of Cse and Technology Greater Noida India ABV-IIITM Gwalior Department of Cse Gwalior India

ISBN: (纸本)9798350360523

A robust watermarking scheme is proposed in this paper. The proposed scheme uses discrete wavelet transformations in conjunction with Hessenberg decomposition and singular value decomposition to decompose the cover image and watermark image. Every single value of the watermark is instantly integrated, utilising the optimal scaling factor, into the solitary component of the cover image after the application of singular value decomposition. To make the attacked watermark image attack-free and high-quality, a robust image reconstruction technique is integrated with the proposed watermarking scheme, considering various image processing and geometrical attack scenarios. The proposed watermarking scheme is more resistant to noise-based attacks, according to experimental findings computed in terms of several performance metrics, including peak signal-to-noise ratio (PSNR), structure similarity index (SSIM), bit error rate (BER), and normalised absolute error (NAE). © 2024 ieee.

关键词： Singular value decomposition

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Design and Application of image Recognition Framework based on Cloud Edge Collaboration in Distribution Stations 5

Design and Application of Image Recognition Framework Based ...

引用

5th ieee international conference on Power, Intelligent Computing and systems, ICPICS 2023

作者： Wu, Wenwei Zhang, Lishou Kang, Kai Liu, Juntao State Grid Shanghai Municipal Electric Power Company Construction and Operation Center Shanghai China Shanghai Yitong Information Technology Co. Ltd R and D Department Shanghai China

ISBN: (纸本)9798350333442

Targeted on the intelligent identification and cloud load reduction requirements of power system in video monitoring, a vision analysis system platform and implementation scheme for distribution station based on cloud edge system are proposed. Through multi-source data fusion analysis, optimization of defect fault location, image recognition algorithm, cloud edge threshold classification collaboration, image processing and feature extraction technologies such as YOLOv3, Mask-CRNN, etc., the high-definition real-time image is analyzed, and the main equipment status recognition and security abnormal behavior recognition functions of the distribution station are realized. The real-time and accuracy of each analysis function is verified by the on-site distribution station, and the relevant experimental results of some functions in the power grid are compared to show the effectiveness of the system scheme. © 2023 ieee.

关键词： internet of things

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Fusion of image and Pointcloud Data for 3D Object Detection with 4D Imaging Radar 2

Fusion of Image and Pointcloud Data for 3D Object Detection ...

引用

2nd ieee international conference on signal, Information and Data Processing, ICSIDP 2024

作者： Li, Xiaozhi Pang, Zhaochen Li, Jian Ministry of Education Beijing China Beijing Institute of Technology School of Computer Science and Technology Beijing China Beijing Institute of Technology Radar Technology Research Institute School of Information and Electronics Beijing China

ISBN: (纸本)9798331515669

3D object detection aims to extract the spatial positions of objects from sensor data, thereby improving environmental awareness and comprehension. With the advancement of radar technology, the 4D imaging radar offers greater robustness in adverse weather conditions compared to LiDAR sensors, thus expanding its potential applications. However, due to the relative scarcity of 4D imaging radar datasets and the inherent sparsity of the radar point clouds, traditional point cloud-based 3D detection models perform suboptimally when applied directly. This paper focuses on the 3D object detection task with multimodal sensors, exploring the integration of RGB image features and 4D imaging radar point cloud features. We propose an innovative multi-modal detection fusion algorithm that markedly enhances detection accuracy on the VoD dataset. © 2024 ieee.

关键词： Radar imaging

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A Novel Federated Learning based Intrusion Detection System for IoT Networks 59

A Novel Federated Learning Based Intrusion Detection System ...

引用

59th Annual ieee international conference on Communications (ieee ICC)

作者： Benameur, Rabaie Dahane, Amine Souihi, Sami Mellouk, Abdelhamid Univ Oran 1 Lab Ind Comp & Networks RIIR Oran Algeria Inst Appl Sci & Technol ISTA Oran Algeria Univ Paris Est Creteil TincNET Res Team Image Signal & Intelligent Syst LiSSi Lab Creteil France

ISBN: (纸本)9781728190549

In the realm of IoT platforms, susceptibility to cyber-attacks is a pressing concern, necessitating the deployment of Intrusion Detection systems (IDS). Constructing a scalable, accurate, and lightweight model without compromising data privacy poses a formidable challenge. This study assesses classical and novel approaches employing federated learning (FL) to train IDS models. Optimization through Knowledge Distillation (KD) techniques aims to enhance computational efficiency. Experimental results reveal the efficacy of federated learning, achieving an 84.5% accuracy for 15 attack types, and an impressive performance for binary network attack classification. Notably, these models exhibit shorter inference times compared to cutting-edge machine learning models trained on the Edge-IIoTset dataset, offering promising advancements in IoT security.

关键词： IoT IDS Deep learning Federated learning Security Edge computing

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FKAN-GMFNet: Fourier Kolmogorov-Arnold-based Group Multi-scale Fusion Network for Aneurysm image Segmentation

FKAN-GMFNet: Fourier Kolmogorov-Arnold-based Group Multi-sca...

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2025 ieee international conference on Acoustics, Speech, and signal Processing, ICASSP 2025

作者： Pang, Shanchen Zhao, Xue Zhang, Yulin Zhao, Yawu Ding, Hengtao Zhao, Zhiyuan Qiao, Sibo Qingdao266580 China College of Mathematics and Systems Science Shandong University of Science and Technology Qingdao266590 China The College of Software Tiangong University Tianjin300387 China

ISBN: (纸本)9798350368741

KAN-based networks, while offering improved interpretability compared to traditional models used in medical image segmentation, often struggle with limited adaptability to diverse imaging environments, making them less ideal for such tasks. To address this issue, we propose a Fourier Kolmogorov-Arnold-based (FKAN) Group Multi-scale Fusion Network, termed FKAN-GMFNet, which incorporates an FKAN layer into a labeled intermediate representation, introducing an Enhanced-FKAN block. Furthermore, we develop the Attention Group Multi-scale Aggregation (ATGMA) module, which leverages attention mechanisms and grouping strategies to effectively fuse feature masks with both high- and low-scale feature information, thereby achieving a comprehensive multi-scale feature representation. Extensive experiments demonstrate that the FKAN-GMFNet significantly outperforms seven state-of-the-art methods in both Dice and IoU scores, where the Dice and IoU scores for the IAS-L dataset are 88.82% and 80.09%, respectively. Code is available at https://***/zx123868/FKAN-GMFNet. © 2025 ieee.

关键词： Fourier Kolmogorov-Arnold Intracranial aneurysms Medical image Segmentation

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