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Video Smoke Detection Algorithm based on a Spatial-Temporal Neural Network Model 9

Video Smoke Detection Algorithm Based on a Spatial-Temporal ...

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9th international conference on Intelligent Computing and signal Processing, ICSP 2024

作者： Cao, Zhen Zhang, Xi Shenyang Fire Science and Technology Research Institute Ministry of Emergency Management Shengyang China

ISBN: (纸本)9798350376548

a kind of spatial-temporal neural network video smoke detection algorithm is proposed in order to solve the problems associated with the incorrect classification of the static approximate smoke background in the face of the detection of smoke in video detection networks, and the problem of false alarms and of the original test model algorithms being different in different detection environments. based on the original YOLO v4 neural network algorithm, this paper introduces a k-means + + algorithm and genetic algorithm, while using the algorithm's clustering function to classify the sample points of the real boxes of the image data set, which make it a more suitable anchor. At the same time, the genetic algorithm is used to adjust its anchor in order to allow the generated anchor to adapt to the needs related to smoke detection. In the original neural network model, the dual-stream network model algorithm is used to extract information from the first step of the YOLO algorithm in order to further filter the smoke's characteristics as well as filter out error information, all to improve the detection capabilities of the overall neural network for video smoke fog images. Compared with traditional YOLOv4 networks, the algorithm obtained by the model algorithm has been improved by 8.51°/0. In actual tests, the alarm time requirements of the smoke alarm test program for early fire monitoring and the alarm systems for visual images were improved, and the detection accuracy of the network was also improved based on the assurance of the detection speed, while the performance of the model algorithm was also improved for different scenes. © 2024 IEEE.

关键词： dual-stream Network K-means safety science smoke detection YOLOv4

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Integration of TinyML-based proximity and couch sensing in wearable devices for monitoring infectious disease’s social distance compliance 23

Integration of TinyML-based proximity and couch sensing in w...

引用

12th international conference on Software and Computer Applications, ICSCA 2023

作者： Umutoni, Ritha M. Ogore, Marvin M. Savanna, Rosette L. Hanyurwimfura, Damien Nsenga, Jimmy Mukanyiligira, Didacienne Nzanywayingoma, Frederic Ngabo, Desire Habiyaremye, Joseph Rwanda Narada LTD

ISBN: (纸本)9781450398589

With the advent of artificial intelligence (AI) and internet of Things (IoT), there has been a rapid increase in the use of sensors to intelligently monitor the environment and movement of objects. Smart solutions have been widely used for monitoring infectious diseases by limiting the transmission of contagious diseases using proximity sensing systems. This is an alternative to conventional social distancing technologies like Bluetooth and cameras which uses machine learning (ML), image processing to identify trespassers, and multiple object detection in real-time. This paper leverages the emerging Tiny ML technology to design and develop a wearable device that can prevent infectious diseases from spreading. The device senses the cough sound of the nearest person within a limited distance and then identify the nearest objects such as humans, animals (dog, goats), and wind-blown vegetation, based on patterns of PIR signals bounced back from different objects. By using machine learning algorithms, the device can be able to notify the user when they are in a safe environment or not. This solution is a wearable device that has the potential to be used in monitoring the transmission of contagious diseases by detecting and identifying moving objects and alerting people to keep their distance when they are in an unsafe environment with a high risk of being exposed to the disease. This work-focused research project will particularly focus on monitoring the risk environment to prevent infectious diseases between humans and between humans and animals, reminding users to keep their distance for their safety and the use of the Convolutional Neural Network (CNN) algorithm on the device for identifying moving objects and for detecting cough. The system has been evaluated, and the experiments have shown a performance accuracy of 92.1% for object detection and 68% for cough detection, promising for detecting a safe environment. This accuracy could be increased over time via reinfo

关键词： Wearable technology

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based on Beidou Short Message of High-precision Landslide Early Warning Information Release technology Research 2

Based on Beidou Short Message of High-precision Landslide Ea...

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2nd international conference on signal image Processing and Communication, ICSIPC 2022

作者： Zhang, Yao Huang, Jianhua Sun, Xiyan Ji, Yuanfa School of Information and Communication Guilin University of Electronic Technology Guilin541004 China National & Local Joint Engineering Research Center of Satellite Navigation Positioning and Location Service Guilin541004 China

ISBN: (纸本)9781510657694

To the high accuracy real-time landslide early warning information sent to the disaster area, reduce the landslide caused loss of life and property of people, design a kind of based on Beidou short message communication mode to release the method of high-precision landslide early warning information, optimize the landslide early warning information release, the standard of Beidou short message protocol and CAP (Common Alerting Protocol) combined general alarm agreement, enrich and perfect the early warning information content, high precision of landslide early warning information for the package transmission, and automatically by the Beidou terminal receipt Beidou short message warning message, implements the information based on internet and Beidou short message communication connectivity, provides the way of warning issued emergency measures, improve the timeliness and reliability of the landslide early warning information release. © 2022 SPIE.

关键词： Landslides

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Improved Dynamic Embedding Scheme with Adaptive Pixel Replacement 17th

Improved Dynamic Embedding Scheme with Adaptive Pixel Replac...

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17th international conference on Intelligent Information Hiding and Multimedia signal Processing (IIH-MSP) / 14th international conference on Frontiers of Information technology, Applications and Tools (FITAT)

作者： Lee, Chin-Feng Shen, Jau-Ji Tsai, Yun-Chin Chaoyang Univ Technol Dept Informat Management Taichung 41349 Taiwan Natl Chung Hsing Univ Dept Management Informat Syst Taichung 402 Taiwan

ISBN: (纸本)9789811910531;9789811910524

The field of information security has gradually been valued in recent years;steganography and cryptography techniques are two popular methods for protecting data privacy. The image has spatial redundancy that is the neighboring pixels in the picture usually have similar intensity. Even the vector quantization-compressed (VQ) image after VQ encoding also has coding redundancy, so there is also a correlation between the index values. based on coding redundancy, we proposed a high-capacity IDES-APR scheme for protecting confidential data. We develop a reduced index strategy to recode the VQ index, by searching for similar index values;the original redundant code is reduced to only three bits. Adjust the VQ image by embedding secret data to create stego image block, which become more similar to the original image blocks after embedding. Compared with other similar work, the proposed scheme preforms better regarding the embedding capacity and image quality.

关键词： Data hiding Steganography Vector quantization (VQ) VQ-based data hiding

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FUGAN: A GAN based Facial Reconstructor for Accurate Unveiling of Hidden Faces 27th

FUGAN: A GAN Based Facial Reconstructor for Accurate Unveili...

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27th international conference on Pattern Recognition, ICPR 2024

作者： Sadhukhan, Mrinmoy Bhattacharya, Indrajit Dutta, Paramartha Department of Computer and System Sciences Siksha Bhavana Visva Bharati Bolpur India Department of Computer Applications Kalyani Government Engineering College Kalyani India

ISBN: (纸本)9783031781711

image-to-image translation has become a prominent trend in the field of computer vision. This innovative technique is widely employed for generating concealed facial features from given noise. It proves particularly useful in reconstructing obscured facial regions covered by masks. The underlying technology at the core of this method is the Generative Adversarial Network (GAN). The primary mechanism of GAN-based neural networks relies on an encoder-decoder structure combined with a discriminator network. The discriminator plays a crucial role in training the network to distinguish between authentic and generated images. FUGAN, a novel approach in this domain, incorporates a self-attention block and has demonstrated superior performance to other models. With an impressive SSIM and BRISQUE score of 0.928 and 27.990, respectively, FUGAN is at the forefront of achieving state-of-the-art results. The architecture of the FUGAN neural network is built upon the UNET framework, with modifications to enhance its effectiveness. These modifications involve increasing the network depth and incorporating batch instance normalization as a regularizer to achieve the desired outcomes. The resulting model attains a smaller size and exhibits high accuracy in image regeneration. This streamlined and efficient FUGAN model is well-suited for deploying low-resource internet of Things (IoT) devices. Its capability to regenerate facial features from masked regions makes it instrumental in surveillance systems, detecting individuals wearing masks and reconstructing their facial details. Github link (FUGAN: https://***/mrinmoy-sadhukhan/FUGAN-model) of our work is provided. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Gallium nitride

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An image Encryption Method based on Logistic Mapping and Phasmatodea Population Evolution Algorithm 17th

An Image Encryption Method Based on Logistic Mapping and Pha...

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作者： Sun, Xiao-xue Song, Pei-Cheng Shieh, Chin-Shiuh Tsai, Pei-Wei Pan, Jeng-Shyang Shandong Univ Sci & Technol Coll Comp Sci & Engn Qingdao 266590 Peoples R China Natl Kaohsiung Univ Sci & Technol Dept Elect Engn Kaohsiung Taiwan Swinburne Univ Technol Melbourne Vic Australia

ISBN: (纸本)9789811910579;9789811910562

The security of information is closely related to our daily life and occupies an important position. The data encryption algorithm is an indispensable element in modern life. image encryption technology is one of the more commonly used technologies and methods in contemporary networks. Since the logistic transformation is sensitive to the initial value, the paper tries to employ the Phasmatodea population evolution (PPE) algorithm to train and select an optimal appropriate initial value to improve security. After the encryption simulation experiment test, the PPE algorithm in this paper has more outstanding encryption performance among several encryption methods, has better scrambling and diffusion effects, and has improved information security.

关键词： Chaos image encryption Logistic mapping Phasmatodea population evolution algorithm

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An IoT based Heart Healthcare Platform for the Sultanate of Oman

An IoT Based Heart Healthcare Platform for the Sultanate of ...

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2022 Mohammad Ali Jinnah University international conference on Computing, MAJICC 2022

作者： Stephen, Vimal Kumar Virutachalam, Mathivanan Manalang, Antonio Rutaf Shaikh, Mohammed Tariq University of Technology and Applied Sciences Department of Information Technology Ibra Oman

ISBN: (数字)9781665475198

ISBN: (纸本)9781665475198

The evolution of the internet of Things (IoT) has been from the convergence of different forms of digital technologies such as embedded systems, real-time analytics, wireless communication, and sensors. The rise of cardiovascular disease (CVD) among adults in Oman has become a growing concern. All IoT-driven healthcare and wellness systems facilitate a continuous form of monitoring of several chronic conditions. The use of IoT healthcare platforms has a huge positive impact in providing timely help and improvement in general well-being. An abnormal situation caused due to irregular heartbeat rate is called arrhythmia and this may become dangerous as the cardiac system is affected due to aging and other pathological and sociological factors. In order to diagnose this abnormality, electrical impulses produced by the heart are recorded by equipment called Electrocardiogram (ECG). A wearable ECG device is used to monitor the patients heartbeats through the IoT platform. The ECG signals to arrhythmia classes are classified using Convolutional Neural Networks (CNN). 1D CNN techniques is used in state-of-the-art modern research, in order to classify this signal. Tabu Search (TS) algorithm with CNN, is used in this work to classify ECG signal image. The evaluation of the technique is done based on performance evaluation matrices which can produce enhanced outcomes, when compared to the present literature. © 2022 IEEE.

关键词： Electrocardiograms

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Improved MDCFT-based Method for Estimating Physical Parameters from Newton's Rings 3

Improved MDCFT-Based Method for Estimating Physical Paramete...

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3rd international conference on Optics and image Processing, ICOIP 2023

作者： Shen, Deming Lu, Mingfeng Wu, Jinmin Xing, Ruoqi Xiong, Xiaoxin Wei, Hongtao Fan, Saihui Zhang, Feng Tao, Ran School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Fractional Signals and Systems Beijing100081 China School of Automation Beijing Information Science & Technology University Beijing100101 China

ISBN: (纸本)9781510667426

Newton's ring pattern is an typical interference fringe often encountered in optical measurements. The physical parameters, such as curvature radius, the ring's center can be estimated by analyzing it. Newton ring formed by spherical interference is two-dimensional Chirp signal, and its chirp parameters are almost impossible to be integers. However, the strict constraints of discrete Chirp Fourier transform (DCFT) and the existing discrete Modified Chirp Fourier transform (MDCFT) can only estimate the integer value part of parameter, which has a large recognition error. An improved MDCFT algorithm is proposed to further estimate the non-integer value part by using the object offset principle, thereby improving the estimation accuracy of Newton ring parameters. Experimental results verify the effectiveness and correctness of the proposed method. © 2023 SPIE. All rights reserved.

关键词： Parameter estimation

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Research on image Denoising Algorithm based on Edge Enhancement Sparse Transform and Low Rank 3rd

Research on Image Denoising Algorithm Based on Edge Enhancem...

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3rd international conference on Advanced Intelligent Technologies, ICAIT 2022

作者： Chen, Yicong Huang, Xiangwei Liu, Cuixiang Shan, Qianqian School of Information Engineering Hebei University of Technology Tianjin China Glasgow College University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9789819952021

Focused on the issue that detailed information of edge is easily lost in the process of image denoising, the image denoising algorithm based on edge enhancement sparse transform and low rank was proposed. Firstly, Canny algorithm was used to gain the image boundary to obtain the edge matrix, and secondly, the Non-subsampled contourlet transform (NSCT) was used to gain the multi-directional high-frequency sub-band map, and then the edge matrix was used to locate the edge position in the high-frequency sub-map. The edge sub-band coefficients were enlarged to enhance the edge to form the edge-enhanced noise image. Finally, the image was divided into image patches, then the local sparsity of image patches to sparse transform and non-local self-similarities of image patches to block match were used to achieve the purpose of image denoising. The experimental results show that, compared with K-Singular Value Decomposition (K-SVD), Group Low-Rank (GLR), Sparsifying Transform Learning and Low Rank (STROLLR), and DnCNN algorithms under different levels of noise, the proposed algorithm not only has a large improvement in the Peak signal-to-Noise Ratio (PSNR), but also maintains clear edge details in visual effects while reducing noise. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： image denoising

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PSO and CPSO based Interference Alignment for K-User MIMO Interference Channel 7

PSO and CPSO Based Interference Alignment for K-User MIMO In...

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7th international conference on image and signal Processing and their Applications, ISPA 2022

作者： Messaoud, Lysa Ait Merazka, Fatiha Usthb University Electrical Engineering Faculty Lisic Lab. Telecommunications Department Algiers16111 Algeria

ISBN: (纸本)9781665480420

This paper investigates how to use a metaheuristic based technique, namely Particle Swarm Optimization (PSO), in carrying out of Interference Alignment (IA) for K-User MIMO Interference Channel (IC). Despite its increasing popularity, mainly in wireless communications, IA lacks explicit and straightforward design procedures. Indeed, IA design results in complex optimization tasks involving a large number of decision variables, together with a problem of convergence of the IA solutions. In this paper, the IA optimization is performed using PSO and Cooperative PSO (CPSO) more suitable for large scale optimization. A comparison between the two versions is also carried out. The cooperative based approach seems promising. © 2022 IEEE.

关键词： MIMO systems

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