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FMCW ice detection radar signal processing based on improved spectrum estimation algorithm

FMCW ice detection radar signal processing based on improved...

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2024 international conference on image, signal Processing, and Pattern Recognition, ISPP 2024

作者： Song, Yibo Dou, Yinke Wang, Yuchen Zuo, Guangyu Guo, Jingxue Zhang, Zidong School of Electrical and Power Engineering Taiyuan University of Technology Taiyuan China Shanxi Energy Internet Research Institute Taiyuan China

ISBN: (纸本)9781510680425

The Antarctic ice sheet is an important part of the Earth system and plays a key role in the global climate system. The frequency modulated continuous wave (FMCW) radar can be used to obtain the changes of the transmitted signals at different layers inside the ice sheet, and then the information of the isochronous layers of the ice sheet can be extracted and the shallow accumulation rate can be deduced. In this paper, an improved spectrum estimation algorithm is proposed, which combines FFT (Fast Fourier Transform) and Chirp-Z (CZT transform, linear frequency modulation transform) to estimate the spectrum of the simulated radar system's difference frequency signals, effectively improving the radar detection accuracy, and verifying the effectiveness and rationality of the algorithm, so that the isochronous layers can be extracted on a larger spatial scale. In China's 36th Antarctic scientific expedition, FMCW radar was used to obtain the distribution of shallow isochronous layers in East Antarctica from Zhongshan Station to Taishan Station. In this paper, taking a typical area as an example, the algorithm was used to obtain the stratification and structure information of the ice sheet on a large-scale space, which provides important data support for the calculation of large-scale accumulation rate and flow history in the Antarctic region. © 2024 SPIE.

关键词： Fast Fourier transforms

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Research on algorithms of the astronautic data acquisition and encoder system based on domestic FPGA and SAD8309 3

Research on algorithms of the astronautic data acquisition a...

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3rd international conference on Electronic Information Engineering, Big Data, and Computer technology, EIBDCT 2024

作者： Zhou, Tianyi Huang, Hongjia Lv, Dun Wang, Xin Bian, Xu Dong, Wentai Wu, Jiayi Beijing Institute of Astronautical Systems Engineering China Academy of Launch Vehicle Technology Beijing China

ISBN: (纸本)9781510680449

Application verification is a key basic task for ensuring component independence. It involves a series of tests, assessments, and comprehensive evaluations of components before they are applied to equipment, to determine the maturity of component development and their suitability for usage. This paper introduces the component application verification work based on the astronautic data acquisition and encoder system, achieving 100% domestication of components and completing two key technological breakthroughs and innovations. The first is a design of an image compression algorithm scheme and an employment of H.264 image compression algorithm, using domestic FPGA to replace the original imported FPGA+DSP scheme. The second is an optimization of the acquisition and encoder precision algorithm, completing filter function based on domestic FPGA. After verification, the image compression effect of the FPGA is better than that of imported products. The statistical compressed image peak signal-to-noise ratio is greater than 30dB, meeting the requirements for usage. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Field programmable gate arrays (FPGA)

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Deep Learning-based Modulation Classification Leveraging Dual-Type image 15

Deep Learning-Based Modulation Classification Leveraging Dua...

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15th international conference on Information and Communication technology Convergence, ICTC 2024

作者： Cho, Yunseol Kim, Hanvit Park, Hyunwoo Park, Jiyeon Ji, Younggun Ju, Hyungjun Choi, Jaekark Im, Sanghun Kim, Kihun Kim, Sunwoo Hanyang University Department of Electronic Engineering Seoul Korea Republic of Tactical Communication System Team Hanwha Systems Seongnam Korea Republic of

ISBN: (纸本)9798350364637

In this paper, we present an automatic modulation classification (AMC) algorithm for identifying overlapped signals. The proposed algorithm leverages dual-type images as deep learning input data, which is composed of spectrogram and signal images. The dual-type images have the features of both individual images, such as frequency change over time and information on amplitude and phase. We improve modulation classification performance by reflecting various features of a single signal. The simulation results show that the proposed algorithm has accurate classification performance compared to single-type input images, especially in analog modulation classification. © 2024 IEEE.

关键词： signal modulation

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Efficient Steganographic Method based on Modulo Cube 1st

Efficient Steganographic Method Based on Modulo Cube

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1st international conference on Security and Information Technologies with AI, internet Computing, and Big data Applications (SITAIBA)

作者： Ko, Hung-Jui Huang, Cheng-Ta Tseng, Hsueh-Wen Wang, Shiuh-Jeng Natl Chung Hsing Univ Dept Comp Sci & Engn Taichung Taiwan Yuan Ze Univ Int Bachelor Program Informat Taoyuan Taiwan Yuan Ze Univ Dept Informat Management Taoyuan Taiwan Cent Police Univ Dept Informat Management Taoyuan Taiwan

ISBN: (纸本)9783031054914;9783031054907

In this paper, we propose a steganographic method with high capacity based on modulo operation. The secret message is mapped to a cube, the coordinates of the position will be calculated by modulo and then embedded in the cover image. The experimental results show that our proposed method can have a higher capacity with imperceptibility. The modulo operation can make the proposed method have lower computational overhead.

关键词： Steganography Modulo operation Magic cube

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Fragile watermarking for medical image authentication based on DCT technique 5

Fragile watermarking for medical image authentication based ...

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5th international conference on Pattern Analysis and Intelligent systems, PAIS 2023

作者： Bouarroudj, Riadh Souami, Feryel Bellala, Fatma Zohra University of Science and Technology Houari Boumediene Computer Science Department Algiers Algeria

ISBN: (纸本)9798350381450

With the advancement of internet and computer technology in the last decade, the ease of editing and altering digital images has significantly increased. Therefore, it is now more crucial than ever for sensitive industries, such as the medical field, to employ image authentication techniques in order to ensure that the images have not been altered. This paper presents a non-blind fragile watermarking technique for medical image authentication. The watermark is generated by downsampling the cover image and embedded into the high-frequency coefficients after applying DCT to the host image. The experimental results demonstrate that the presented technique produces a high watermarked image quality and offers a high sensitivity to various attacks like JPEG compression, collage, and vector quantization. Furthermore, the model localizes with high accuracy the tampered areas within the attacked image. © 2023 IEEE.

关键词： Authentication

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Compressive sensing based sparse representation analysis for remote sensing SAR imagery

Compressive sensing based sparse representation analysis for...

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2024 international conference on Remote Sensing, Mapping, and Geographic Information systems, RSMG 2024

作者： Yin, Hang Wang, Jue Wen, Xinyi Xie, Xinran Space Engineering University Beijing101407 China

ISBN: (纸本)9781510685826

The signal processing technology of Compressive Sensing (CS) overturns the limitation of the traditional sensing method that only high sampling rate can achieve high resolution. The compressive sensing method saves internal storage and resources of information processing due to the small amount of data processed. Applying CS to spaceborne Synthetic Aperture Radar (SAR) system can effectively reduce the pressure of hardware platform. Sparse representation of SAR image is a prerequisite for CS application in remote sensing SAR imagery, which is analyzed quantitatively under different orthogonal bases and representation approach. The effect analysis is measured by the evaluation indexes such as peak signal-to-noise ratio, structural similarity and edge retention index. The simulation results show that the effect of sparse representation can meet the quality and structure requirements of SAR images in most cases. The conclusion verifies that SAR images satisfy CS requirement for sparsity, which supports the further study of CS reconstruction application in spaceborne SAR image. © 2024 SPIE.

关键词： Digital storage

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A Denoising Method from Low-dose CT images based on Improved U-Net with Attention Mechanism 13

A Denoising Method from Low-dose CT Images Based on Improved...

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Joint 13th international conference on Soft Computing and Intelligent systems and 25th international Symposium on Advanced Intelligent systems, SCIS and ISIS 2024

作者： Sawada, Shuji Li, Guangxu Murakami, Seiichi Kamiya, Tohru Kyushu Institute of Technology Mechanical and Control Engineering Fukuoka Kitakyushu Japan Tiangong University Electronics and Information Engineering XiQing Tianjin China Junshin Gakuen University Fukuoka Radiological Science Faculty of Health Sciences Fukuoka Japan

ISBN: (纸本)9798350373332

Japan has the highest number of CT scanners per million population among developed countries, and the annual medical radiation dose is about four times the world average. Screening of high-risk populations with low-dose CT has been shown to reduce lung cancer mortality. However, in order to obtain image quality comparable to that of normal-dose CT, it is necessary to accurately estimate the image noise of low-dose CT. In this paper, we apply a noise reduction method using convolutional neural networks: the CNN model is based on U-Net, a fully convolutional network with encoder-decoder structure, with two convolutional layer modifications and three attention mechanisms. Experimental results using whole body slice CT images of piglets show that the proposed method is useful by comparing with CT images of normal dose and by evaluating image quality using peak signal-to-noise ratio (PSNR). © 2024 IEEE.

关键词： Computerized tomography

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2023 5th international Symposium on signal Processing systems, SSPS 2023

2023 5th International Symposium on Signal Processing System...

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5th international Symposium on signal Processing systems, SSPS 2023

ISBN: (纸本)9798400700040

The proceedings contain 11 papers. The topics discussed include: accurate shadow height measurement technology of the SAR image;millimeter wave radar fall detection algorithm based on improved transformer;an end-to-end learning based covolutional neural network for single image defogging algorithm;ornaments and barlines recognition of numbered musical notation using YOLOv5;study on hyperspectral remote sensing images of GF-5 de-blurring based on sparse representation;design and implementation of target tracking system in low illumination environment based on FPGA;SAR image geometry correction technology based on block parallel signal processing;speech recognition method based on deep learning of artificial intelligence: an example of BLSTM-CTC model;and high precision reference measurement technology for mechanical scanning radar.

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The Method of Industrial internet image Super-resolution based on Transformer 16

The Method of Industrial Internet Image Super-resolution Bas...

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16th IEEE international conference on signal Processing (ICSP)

作者： Liu, Lin Yu, Yingjie Wang, Juncheng Jin, Yi Zeng, Yuqiao China Automot Technol & Res Ctr Co Ltd Automot Data China Tianjin Co Ltd Tianjin Peoples R China Beijing Jiaotong Univ Inst Informat Sci Beijing Peoples R China

ISBN: (数字)9781665460569

ISBN: (纸本)9781665460569

As a fundamental task in the field of computer vision, super-resolution reconstruction has a wide range of applications on the industrial internet. However, most of the existing super-resolution reconstruction methods are based on convolutional neural networks for feature extraction, which have the problems of low model representation efficiency and insufficient explanation of the extraction process, which limit the performance of the model in industrial internet scenarios. In recent years, although transformers have been proposed to solve the above problems well and achieve good results in image classification tasks, there is still room for improvement in the adaptability of super-resolution reconstruction tasks. Therefore, in this paper, an improved transformer-based image super-resolution reconstruction model is designed to effectively improve the performance of the image super-resolution reconstruction model. Experiments show that the adaptation of the Transformer mechanism on the super-resolution reconstruction task in this paper can practically improve the performance of the model on public datasets and industrial internet scenario datasets.

关键词： Super-resolution Reconstruction Transformer Technologies Industrial internet

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Smart IoT-based Emotion Sensing Wearable: Revolutionizing Emotional Well-Being 2

Smart IoT-Based Emotion Sensing Wearable: Revolutionizing Em...

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2nd international conference on Recent Trends in Microelectronics, Automation, Computing, and Communications systems, ICMACC 2024

作者： Kannapiran, Pritika Roy, Sritama School of Computer Science and Engineering Vellore Institute of Technology Chennai India School of Electronics Engineering Vellore Institute of Technology Chennai600127 India

ISBN: (纸本)9798350366570

In the fast-paced world of today, mental health has become a critical issue, with emotional stability being a key component of general health. Traditional methods of detecting and managing emotions often fall short due to their reliance on verbal and facial cues, leaving individuals with conditions such as Alexithymia or Autism Spectrum Disorder (ASD) at a disadvantage. This paper introduces a novel solution: the Smart IoT-based Emotion Sensing Wearable, is designed to revolutionize emotional sensing and management. The primary goal of the research is to create a wearable gadget that can track vital signs and instantly identify different emotions. Using the internet of Things (IoT), machine learning, and cloud computing, this wearable device bridges the gap for people with special needs and improves emotional understanding for all users by providing real-time emotion recognition and targeted help. © 2024 IEEE.

关键词： Emotion Recognition

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