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检索条件"任意字段=IEEE International Conference on Signal Image Technology and Internet Based Systems"

共 20446 条记录，以下是71-80 订阅

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Key-Independent image Encryption using DNA Encoding and Chaotic Dynamics 10

Key-Independent Image Encryption using DNA Encoding and Chao...

引用

10th international conference on Communication and signal Processing, ICCSP 2024

作者： Maharaja Vannia Moorthi, V. Krishna, Megha R. Kumar, Gopika Anil Thanikaiselvan, V. Subashanthini, S. Amirtharajan, Rengarajan Vellore Institute of Technology School of Electronics Engineering Vellore India Vellore Institute of Technology School of Computer Science Engineering and Information Systems Vellore India Sastra Deemed University School of Electrical & Electronics Engineering Thanjavur613 401 India

ISBN: (纸本)9798350353068

Privacy violations are common in our technology-driven world, where almost everyone interacts with internet-connected electronic devices. To address this, cryptography has emerged, concealing data during transmission to deter hackers. Cryptography involves basic mathematical operations, exchanging data based on a shared key known only to the sender and receiver. However, this method suffers from key dependency at the receiver's end, requiring constant key knowledge. To overcome this issue, a novel image encryption method has been introduced in this paper that is independent of the key on the receiver side. This method leverages techniques such as DNA Encoding, Chaotic Dynamics, and Key Hiding Mechanisms to increase the security of the sent image. The proposed method has been tested experimentally, and the results demonstrate its effectiveness with entropy values exceeding 7.995 and correlation coefficient values below 1% for the vertical, horizontal, and diagonal directions. Overall, the proposed image encryption scheme offers a promising solution for protecting sensitive image data in various applications, combining advanced encryption techniques with key management enhancements to ensure confidentiality and integrity. © 2024 ieee.

关键词： Cryptography

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CONTENT-AWARE SUPERVISION FOR DIFFUSION-based RESTORATION OF EXTREMELY COMPRESSED BACKGROUND FOR VCM 31

CONTENT-AWARE SUPERVISION FOR DIFFUSION-BASED RESTORATION OF...

引用

2024 international conference on image Processing

作者： Dao, Le Thi Hue Vien, An Gia Lee, Jooyoung Jeong, Seyoon Yang, Naeun Lee, Chul Dongguk Univ Dept Multimedia Engn Seoul South Korea Elect & Telecommun Res Inst Daejeon South Korea

ISBN: (纸本)9798350349405;9798350349399

We propose content-aware supervision (CAS) techniques for diffusion-based restoration of an extremely compressed background for video coding for machines (VCM). First, we develop a CAS block to exploit prior information in an input image to reconstruct the noisy image, which is used as the input for the pretrained diffusion model. Then, we construct a refinement block to guide the pretrained diffusion model at each diffusion step by incorporating a degradation model and correction gradient estimation. Experimental results demonstrate the proposed algorithm outperforms state-of-the-art algorithms.

关键词： image generation image restoration video coding for machines (VCM) diffusion model

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Array Patch Antenna in Ka Band internet Satellite Application 8

Array Patch Antenna in Ka Band Internet Satellite Applicatio...

引用

8th ieee international conference on image and signal Processing and their Applications, ISPA 2024

作者： Kourdi, Zakarya Irid, Hadj Sidi Mohammed Boukhris, Chaima Bouachra, Marwa Algerian Space Agency Dept. Telecom of Satellite Development Center Oran Algeria Faculty Abou-Bekr Belkaid University Dept. Telecommunication of Technology Tlemcen Algeria

ISBN: (数字)9798350309249

ISBN: (纸本)9798350309249

This paper presents a new, compact, single-device array antenna for Ka-band internet applications. The proposed model operates without routing, streamlining deployment and usage. The antenna's features are engineered to enhance its performance, representing a significant advancement in the field. Additionally, the antenna design is precisely tailored to meet the strict requirements of the Algerian satellite ALCOMSAT, ensuring optimal compatibility and performance. The prototype was designed using RO4003 substrate in order to minimize losses and stabilize the structure. © 2024 ieee.

关键词： Satellites

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WAVELET-GUIDED ACCELERATION OF TEXT INVERSION IN DIFFUSION-based image EDITING 49

WAVELET-GUIDED ACCELERATION OF TEXT INVERSION IN DIFFUSION-B...

引用

49th ieee international conference on Acoustics, Speech, and signal Processing (ICASSP)

作者： Koo, Gwanhyeong Yoon, Sunjae Yoo, Chang D. Korea Adv Inst Sci & Technol KAIST Daejeon South Korea

ISBN: (纸本)9798350344868;9798350344851

In the field of image editing, Null-text Inversion (NTI) enables fine-grained editing while preserving the structure of the original image by optimizing null embeddings during the DDIM sampling process. However, the NTI process is time-consuming, taking more than two minutes per image. To address this, we introduce an innovative method that maintains the principles of the NTI while accelerating the image editing process. We propose the WaveOpt-Estimator, which determines the text optimization endpoint based on frequency characteristics. Utilizing wavelet transform analysis to identify the image's frequency characteristics, we can limit text optimization to specific timesteps during the DDIM sampling process. By adopting the Negative-Prompt Inversion (NPI) concept, a target prompt representing the original image serves as the initial text value for optimization. This approach maintains performance comparable to NTI while reducing the average editing time by over 80% compared to the NTI method. Our method presents a promising approach for efficient, high-quality image editing based on diffusion models.

关键词： image editing Null-Text Inversion text optimization diffusion model

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Attention-based UNet enabled Lightweight image Semantic Communication System over internet of Things 25

Attention-based UNet enabled Lightweight Image Semantic Comm...

引用

ieee Wireless Communications and Networking conference (ieee WCNC)

作者： Ma, Guoxin Tong, Haonan Yang, Nuocheng Yin, Changchuan Beijing Univ Posts & Telecommun Beijing Lab Adv Informat Network Beijing Peoples R China

ISBN: (纸本)9798350303582;9798350303599

This paper studies the problem of the lightweight image semantic communication system that is deployed on internet of Things (IoT) devices. In the considered system model, devices must use semantic communication techniques to support user behavior recognition in ultimate video service with high data transmission efficiency. However, it is computationally expensive for IoT devices to deploy semantic codecs due to the complex calculation processes of deep learning (DL) based codec training and inference. To make it affordable for IoT devices to deploy semantic communication systems, we propose an attention-based UNet enabled lightweight image semantic communication (LSSC) system, which achieves low computational complexity and small model size. In particular, we first let the LSSC system train the codec at the edge server to reduce the training computation load on IoT devices. Then, we introduce the convolutional block attention module (CBAM) to extract the image semantic features and decrease the number of downsampling layers thus reducing the floating-point operations (FLOPs). Finally, we experimentally adjust the structure of the codec and find out the optimal number of downsampling layers. Simulation results show that the proposed LSSC system can reduce the semantic codec FLOPs by 14%, and reduce the model size by 55%, with a sacrifice of 3% accuracy, compared to the baseline. Moreover, the proposed scheme can achieve a higher transmission accuracy than the traditional communication scheme in the low channel signal-to-noise (SNR) region.

关键词： Semantic communication image segmentation Attention Mechanism internet of Things

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An image encryption algorithm based on non-degenerate chaos and dynamic Bi-directional permutation 16

An image encryption algorithm based on non-degenerate chaos ...

引用

16th international conference on signal Processing systems, ICSPS 2024

作者： Liao, Yunlong Xu, Qingyang Zhang, Qiyuan Xing, Zheng Yuan, Xiaochen Faculty of Applied Sciences Macao Polytechnic University China

ISBN: (纸本)9781510689251

In the wake of the accelerated advancement of internet of Things(IoT) technology, a significant volume of multimedia information is emerging as the dominant component of IoT applications. However, this information also led to big security risks. Therefore, a secure and reliable image encryption scheme based on non-degenerate hyper chaos and dynamic bidirectional permutation is proposed for the characteristic of digital images which the primary information carrier in the IoT communication environment. The scheme uses non-degenerate discrete chaos to generate pseudo-random sequences and applies them to the encryption process involving image confusion, dynamic permutation, and dynamic diffusion. Through theoretical analysis and experimental verification, the algorithm exhibits high sensitivity to both the plaintext images and the ciphertext images. Concurrently, it can effectively resist common noise attacks and cryptographic attacks. In conclusion, the proposed scheme offers superior encryption capabilities and stands as a secure solution, compatible with a diverse range of IoT environments. © 2025 SPIE.

关键词： Chaos theory

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Leveraging Stable Diffusion with Context-Aware Prompts for Semantic Communication 21

Leveraging Stable Diffusion with Context-Aware Prompts for S...

引用

21st ieee international conference on Mobile Ad-Hoc and Smart systems (MASS)

作者： Nguyen, Long V. Nguyen, Tuan T. Dobre, Octavia A. Duong, Trung Q. Mem Univ St John NF Canada Univ Greenwich London England

ISBN: (纸本)9798350363999;9798350364002

Semantic communication in wireless image transmission leverages the meaning embedded in the image data, aiming to compress, transmit, and reconstruct images based on their semantic content rather than purely pixel data. This paradigm shift allows more efficient utilization of bandwidth and computational resources, focusing on extracting key features and contextual information that is critical for ensuring that the essential content of the image is preserved and accurately conveyed. In this study, we present a novel Stable Diffusion-based semantic communication (SDSC) framework that demonstrates high performance, characterized by an elevated bandwidth compression ratio (BCR) and robust noise tolerance achieved by diffusion mechanism integrating supplementary prompts. Our approach utilizes pre-trained modules of a Variational autoencoder (VAE) and a modified U-shaped network (UNet) to enable robust semantic encoding, decoding, and effective channel denoising. This scheme significantly enhances the system's ability to preserve data integrity and meaning in noisy environments. By introducing additional context-aware prompts during transmission, we improve the accuracy of received information and mitigate the adverse effects of interference and noise. Extensive simulations show that our framework outperforms previous innovative models, demonstrating superior communication fidelity and efficiency under various challenging conditions.

关键词： Semantic communication wireless image transmission stable diffusion joint source-channel coding

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A Grouping Strategy-based Progressive Fusion Network for Hyperspectral image Super-Resolution

A Grouping Strategy-Based Progressive Fusion Network for Hyp...

引用

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

作者： Lv, Guohua Zhang, Baodong Gao, Yongbiao Zhao, Guixin Wang, Guotao Wang, Juncan Jinan China Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing Shandong Fundamental Research Center for Computer Science Jinan China Shandong Key Laboratory of Ubiquitous Intelligent Computing Jinan China Ministry of Education China Beihang University Beijing China

ISBN: (纸本)9798350368741

Hyperspectral super-resolution involves combining low-resolution hyperspectral images with high-resolution multispectral images to produce a high-resolution hyperspectral image. Recently, although many methods for hyperspectral image super-resolution have been proposed, they often fail to fully utilize the high similarity among adjacent bands to enhance fusion performance. Therefore, we propose a grouping strategy-based progressive fusion network (GPFNet) for hyperspectral super-resolution. The core of GPFNet is the grouping strategy fusion block (GPF block), in which grouping-based spatial-spectral information fusion and spatial information refinement are performed. We design the spatial-spectral information fusion module (SSIFM) based on grouped convolutions to capture the feature differences from adjacent bands. To refine spatial details, we develop the spatial information enhancement module (SpaEM), which leverages the hierarchical features extracted by the multi-scale feature extraction module (MIEM). Additionally, a progressive fusion strategy, which involves using multiple upsampled hyperspectral images and downsampled multispectral images, further preserves spectral integrity and spatial details. Extensive experiments show that GPFNet outperforms state-of-the-art methods both qualitatively and quantitatively. © 2025 ieee.

关键词： group convolution Hyperspectral image image fusion super-resolution

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Acoustic signal Processing using Deep Learning for Intelligent Feed Monitoring of Dicentrarchus Labrax 17

Acoustic Signal Processing using Deep Learning for Intellige...

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17th international conference on signal-image technology and internet-based systems, SITIS 2023

作者： Bies, Laura Guruprasad, Shreyas Mysore Ingale, Mrudula Werth, Dirk August-Wilhelm Scheer Institute Saarbrücken Germany

ISBN: (纸本)9798350370911

Acoustic signal processing holds significant promise for real-time fish feeding intensity estimation in aquaculture. Unlike traditional methods reliant on visual cues or sensor data, acoustic analysis provides valuable insights into feeding behavior and demand. By capturing indicators such as water splashing, acoustic techniques can estimate the current feeding demand of fish. Acoustic techniques in aquaculture remain under explored, especially those delving into temporal information within acoustic spectrograms. This paper presents an intelligent monitoring approach using deep learning and acoustic signals. It investigates the perceptual domain of fish feeding acoustic spectrum recognition, extracting insights from Mel Spectrogram feature maps. Employing a supervised machine learning method with a multi-instance multi-label technique, the study classifies audio events during operational scenarios. Furthermore, the research assesses the effectiveness of the proposed neural network (NN) models for multi-label classification by comparing it with established NN architectures like AlexNet, ResNet18, and VGG11, showcasing its superior performance. © 2023 ieee.

关键词： Feeding

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Equipment Fault image Recognition Method based on Deep Integrated Learning with Hyperparameter Optimization 6

Equipment Fault Image Recognition Method Based on Deep Integ...

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6th ieee international conference on Power, Intelligent Computing and systems, ICPICS 2024

作者： Chen, Pintong Guan, Di Chen, Jing Guangdong University of Technology Guangzhou China Liaoning Technical University Huludao China Harbin Institute of Technology Weihai China

ISBN: (纸本)9798350374315

In order to solve the problem of low precision and low stability of deep learning network for industrial equipment fault recognition under strong background noise, a method of equipment fault image recognition based on deep integrated learning with hyperparameter optimization was proposed. Firstly, the time-frequency image data set is constructed by using two-dimensional wavelet transform of the original vibration signal. Secondly, the noise resistance of each CNN network architecture is tested, and the change of network performance is studied by embedding different noise intensities into the data. Then, group optimization algorithm is used to optimize the learning rate and batch sampling parameters of the optimal architecture model. Finally, decision fusion is used to integrate the trained model, so as to improve the stability and image recognition accuracy of the integrated network. Verified by the bearing data of Western Reserve University, the proposed algorithm has good diagnostic accuracy and stability. © 2024 ieee.

关键词： Wavelet transforms

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