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Attributes and Semantic Constrained GAN for Face Sketch-Photo Synthesis 14

Attributes and Semantic Constrained GAN for Face Sketch-Phot...

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14th ieee international conference on Wireless Communications and signal processing (WCSP)

作者： Zheng, Jieying Li, Haoxian Liu, Feng Nanjing Univ Posts & Telecommun Jiangsu Key Lab Image Proc Image Commun Nanjing Peoples R China Nanjing Univ Posts & Telecommun Sch Geog & Biol Informat Nanjing Peoples R China Nanjing Univ Posts & Telecommun Smart Hlth Big Data Anal & Locat Nanjing Peoples R China

ISBN: (纸本)9781665450850

Face sketch-photo synthesis aims at generating a facial photo conditioned on a given photo. It has attracted wide attention in computer vision and has been widely applied in law enforcement and entertainment. However, precisely synthesizing high-quality face photos is still challenging due to the missing color information in face sketches. To alleviate the problem, we propose an attribute and Semantic constrained Generative Adversarial Networks (ASGAN), which introduces face attribute and semantic constraints to improve the quality and accuracy of synthesized photos. Specifically, We first annotate the key attributes in the dataset and form a 14-dimensional attribute vector for each face. Then, the attribute features and semantic features obtained by face parsing are fused. Finally, the generator takes the fused constrain features and sketches as input and constructs two-stream encoders to synthesize high-quality photos. Extensive experimental results demonstrate that our method can significantly outperform state-of-the-art methods. It can synthesize higher-quality face photos while maintaining the identity, attributes, and structure. Meanwhile, it can alleviate the problem of background and skin color synthesis errors.

关键词： face sketch-photo synthesis attribute generative adversarial networks face parsing

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Analysis of Different Encryption Techniques used in Watermarking Algorithm for the Security of Medical image 10

Analysis of Different Encryption Techniques used in Watermar...

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10th international conference on Emerging Trends in Engineering and Technology - signal and Information processing, ICETET-SIP-22 2022

作者： Pulgam, Namita D. Shinde, Subhash K. Ramrao Adik Institute of Technology D y Patil Deemaed to Be University Computer Engineering Navi Mumbai India Lokmanya Tilak College of Engineering Computer Engineering Navi Mumbai India

ISBN: (纸本)9781665467414

Today, in the computerized age, the development and use of internet technology in healthcare has been increasing rapidly. Quick improvement is going on in the telemedicine field with a clear goal to design integrated applications in diagnostics and treatment. Hence medical images are preserved in databases for some time so that post diagnosis treatment will become easier for the patient and for doctors as well. During the process of the treatment patients tend to take experts' advice and that time images of the reports will be shared from one hospital to another. With the use of sharing and transmission technique post treatment cost gets reduced whereas increases the issue concerning the security of patients medical reports. It is important to keep track of images shared between two medical centers to identify sources of image generation as well as protecting patient's sensitive information from intruders or hackers against unauthorized access and modification. Digital watermarking can be used to provide ownership and copyright protection. In the watermarking system image or text can be inserted in the cover image to get a watermarked image. The watermark image or secret image to be inserted can be protected with encryption technique. Hence this paper presents a digital watermarking system designed with encryption techniques to provide security to patients' medical records. The system is evaluated by implementing it with various encryption techniques like Advanced Encryption Standard (AES) with 256 bits, AES-GCM, Triple Data Encryption Standard (TDES), Blowfish etc. The performance of the system is measured with PSNR and SSIM and assessment of the evaluation parameters shows that AES encryption is better in comparison with TDES and Blowfish. © 2022 ieee.

关键词： Telemedicine Watermarking Information processing Copyright protection Market research Robustness Encryption

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Enhanced Video Streaming Based Computing Encoder for Digital Visual processing 2

Enhanced Video Streaming Based Computing Encoder for Digital...

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2nd ieee international conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Kumar, Tarun Shukla, Amita Galgotias University Department of Computer Science and Engineering Greater Noida India Noida Institute of Engineering and Technology Department of Computer Science and Business System Greater Noida India

ISBN: (纸本)9798350347456

The rise of video streaming for digital visual processing has been a boon for the industry of visual processing. Video streaming technology has made it easier for companies to capture, analyze, and interpret visual data faster than ever before. It has allowed for the storage and transmission of large amounts of visual data at high speeds, providing businesses with the ability to process and interpret this data in real-time. Video streaming technology can be used in a wide variety of applications, including facial recognition, 3D mapping, and object recognition. By streaming video data, companies can quickly and accurately identify individuals, recognize objects, and track movement. This technology can also be used in security applications, such as surveillance and monitoring, as well as in medical imaging, such as MRI and CT scans. Video streaming technology has also allowed companies to create more efficient visual processing systems. The streaming video data can be used to automate the process of image recognition and object classification. This has allowed companies to reduce the amount of time and effort needed to interpret visual data. Additionally, streaming video data can be used to create virtual reality experiences, providing users with an immersive experience when viewing digital images. © 2023 ieee.

关键词： Video streaming

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The design of rotation-symmetric Gaussian low-pass filter (RSGLPF) and its applications 23

The design of rotation-symmetric Gaussian low-pass filter (R...

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6th international conference on signal processing and Machine Learning, SPML 2023

作者： Xia, Tongnan Liu, Ming Sun, Jie Huang, Enruo Liang, Shaolin Sun, Yaojie School of Information Science and Technology Institute for Six Sector Economy Fudan University China Department of Health Management Center Zhongshan Hospital Fudan University Shanghai Engineering Research Center of Ai Technology for Cardiopulmonary Diseases Zhongshan Hospital China School of Information Science and Technology Fudan University Fudan China Shanghai Xiazhi Information Technology CO.LTD China STI-ZHILIAN Research Institute for Innovation and Digital Health China and Institute for SIX-SECTOR Economy Fudan University Shanghai China

ISBN: (纸本)9798400707575

In this study, a rotation-symmetric Gaussian low-pass filter (RSGLPF) is designed, and two application methods of the filer are provided. The results of the two methods are different, and researchers and engineers can choose which method to use according to their own needs. In data related research, noise reduction is one of the key steps in most data processing. However, for many non-data processing researchers, it is crucial to choose a simple and effective noise reduction algorithm. Additionally, traditional Gaussian filters could cause some degree of detail damage in the image, we have provided a method to effectively solve this problem. In the present research, there are many low-pass filters. Some of them have simple applications, but the filtering effect may not be very obvious. Others have complex application processes or require high parameter settings. Our research results have both a significant filtering effect and an easy-to-use application process. Even non-experts in this field can apply by following the steps. Moreover, the traditional Gaussian filter will cause some detail damage to images in the process of denoising. We have provided a method that can effectively reduce the detail damage of the original image. Gaussian filter, as a linear smoothing filter, is suitable for eliminating Gaussian noise and has been widely used in image processing, signal processing and other fields.[1, 3] Therefore, our (RSGLPF) is improved on the original Gaussian filter, and can be better applied to the noise reduction process. The results can also show that the denoising effect is indeed more obvious. The results show that the image is smoother, the boundary is more blurred, and the high-frequency signal of the waveform is greatly reduced. The research results provided a practical algorithm model for denoising in signal processing. © 2023 ACM.

关键词： Low pass filters

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Performance Analysis of image Denoising Techniques in Skin Cancer Detection 4th

Performance Analysis of Image Denoising Techniques in Skin C...

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4th international conference on Data, Engineering, and applications, IDEA 2022

作者： Patil, Sheetal Nana Patil, Hitendra D. India

ISBN: (纸本)9789819724505

Because visual information is increasingly being sent in digital image format, identifying noisy data becomes a prevalent difficulty in many research and application sectors. To reduce noise while maintaining image information, many noise reduction techniques have been developed in the modern period. Researchers always struggle with the challenge of noise removal from original image. This study proposed a pre-processing method to improve image quality in terms of performance parameters, making the subsequent image processing work in the diagnosis of any type of skin cancer easier. The major focus of this work is on image denoising or filtering, which improves image quality for subsequent image processing processes in the diagnosis of normal vs. malignant skin. Objectives: To calculate various denoising performance parameters like peak signal to noise ratio (SNR), mean square error (MSE), normalized root mean square error (NRMSE), and others. Methods: In this research work, image denoising technique was performed by using different types of noises and filters. Statistical Analysis: In this research work, we found observational outcomes after noise addition to skin images in terms of pixel value, darkness, brightness related to each pixel. Gaussian and median filter gives MSE between 0 and 17%, NRMSE ranges between 0.025 and 0.425, and PSNR is obtained from Min 15 dB to Max 40 dB. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Median filters

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Hyperspectral image Classification Using Multi-feature Fusion Residual Hypergraph Convolution Network 8

Hyperspectral Image Classification Using Multi-feature Fusio...

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8th international conference on signal and image processing, ICSIP 2023

作者： Zhu, Tianxing Liu, Qin Zhang, Lixiang Tongji University School of Software Engineering Shanghai China Northwestern Polytechnical University School of Computer Science Xi'an China

ISBN: (纸本)9798350397932

Convolutional neural network (CNN) has been broadly adopted on hyperspectral image (HSI) processing due to its impressive feature extraction capabilities. Nevertheless, it is still a challenge for CNN-based hyperspectral image classification methods to extract more effective spectral-spatial features considering all spectral bands. The recent advances of graph convolutional neural networks (GCN), a combination of CNN and graph representation learning, have shown great potential in the HSI. However, the existing GCN-based methods have lower accuracy than the mature CNN methods due problems such as overdependence on the adjacency matrix, usage of a single modal feature. In this paper, we propose the Multi-Feature Fusion Residual Hypergraph Convolution Network (MF-RHCN) for HSI classification. We present a novel Hypergraph Convolution Network that fuses multimodal features effectively, and automatically updates the hyperedge weights, which solves the difficulties encountered by the previous GCN-based hyperspectral classification methods. MF-RHCN first generates hyperedges from features of different modalities to construct a hypergraph representing multimodal features in HSI. Then, the HSI and the extracted hypergraph are input into the hypergraph convolutional neural network for learning. We enhance the hypergraph convolutions with residual connection and input mapping, which helps reduce the over-smoothing issue associated with deep hypergraph models. Sufficient experiments on three datasets have proved the effectiveness of MF-RHCN. © 2023 ieee.

关键词： Convolution

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Linearly Polarized Dual Band Smart Antenna for Wi-Fi and Wi-MAX applications

Linearly Polarized Dual Band Smart Antenna for Wi-Fi and Wi-...

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2023 international conference on signal processing, Computation, Electronics, Power and Telecommunication, IConSCEPT 2023

作者： Chandrasekhar, M. Udaykiranray, P. Laxmi Lahari, J. Sahithi Priya, A. Jyoshna, Ch. Suneel Raja, M. Kakatiya Institute of Technology and Science Dept. of ECE Telangana Warangal506015 India Kakatiya Institute of Technology and Science Telangana Warangal506015 India Dept. of ECE NEC A.P Narasaraopet India

ISBN: (纸本)9798350312126

The design of a dual band patch antenna is with an arced H shaped slot for wireless applications, like Wi-Fi and Wi-MAX is introduced. To Figure out how the performance of the antenna is controlled and operated, a systematic parametric analysis is done on the newly designed microstrip smart antenna. The design and simulations of this antenna are done using Ansys HFSS software. The designed antenna operates at 2.4GHz with a reflection coefficient of -23.34 dB and 5.29GHz with a reflection coefficient of-32.5dB for Wi-Fi and WiMAX applications respectively. © 2023 ieee.

关键词： Slot antennas

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COMPACT AND ADAPTIVE MULTIPLANE imageS FOR VIEW SYNTHESIS

COMPACT AND ADAPTIVE MULTIPLANE IMAGES FOR VIEW SYNTHESIS

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ieee international conference on image processing (ICIP)

作者： Navarro, Julia Sabater, Neus InterDigital Wilmington DE 19809 USA

ISBN: (纸本)9781665441155

Recently, learning methods have been designed to create Multiplane images (MPIs) for view synthesis. While MPIs are extremely powerful and facilitate high quality renderings, a great amount of memory is required, making them impractical for many applications. In this paper, we propose a learning method that optimizes the available memory to render compact and adaptive MPIs. Our MPIs avoid redundant information and take into account the scene geometry to determine the depth sampling.

关键词： View Synthesis Multiplane image

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Filtering Techniques to remove Noises from an image

Filtering Techniques to remove Noises from an Image

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2022 ieee international conference on Advances in Computing, Communication and Applied Informatics, ACCAI 2022

作者： Soora, Narasimha Reddy Vodithala, Swathy Badam, Jwala Sri Hari KITS Dept. of CSE Warangal India

ISBN: (纸本)9781665495295

Now a days a lot real world applications are based on image processing. In image processing after image acquisition, the next step is pre-processing stage. The main objective of pre-processing stage is to make the image appear visually better to the end user by removing noise using various filtering techniques. Filtering techniques change the look and feel of the image using its pixel information. There are various kinds of noise present in an image like salt pepper noises, blur, Gaussian noises, periodic noises, etc. These noises can be removed by various kinds of spatial and frequency domain filtering techniques like mean filters, median filters, Weiner filters and many more. This paper presents the effect of various kinds of filtering techniques on noisy images. © 2022 ieee.

关键词： Median filters

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Improved Breast Cancer Detection in Ultrasound images Using Masked image Integration and Transfer Learning 4

Improved Breast Cancer Detection in Ultrasound Images Using ...

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4th international conference on Robotics, Electrical and signal processing Techniques, ICREST 2025

作者： Shuvo, H.M. Maruf Rahman Islam, Md. Nazmul Biswas, Sunirmal Kumar Islam, Md. Shafiqul Dhaka Bangladesh Electrical and Electronic Engineering Prime University Dhaka Bangladesh Biomedical Physics and Technology University of Dhaka Dhaka Bangladesh

ISBN: (纸本)9798331530938

An early diagnosis is essential for the effective treatment of breast cancer, which is one of the most commonly prevalent cancers in women. In this study, we propose a Deep Learning Transfer Learning technique for segmenting breast cancer tumors from Ultrasound images. To enhance efficiency, we also added masked images with the ultrasound images as a novel strategy. Our main goal is to produce better outcomes with fewer images. To begin with, a straightforward CNN model is created to segment the tumors. To segregate the tumors from the ultrasound and masked images, we next examine how well several Pretrained models, including VGG16, ResNet50, XceptionNet, EfficientNetB7, and ConvNeXtBase, perform. Using metrics like as Accuracy, Precision, Recall and F1-score we evaluate each model's performance. Our findings demonstrate that transfer learning-based approaches perform better than the straightforward CNN model in terms of Accuracy and F1-Score, and that using masked images in addition to the ultrasound images enhances performances even more. EfficientNetB7, which has an F1-Score of 0.9750 and an overall Accuracy of 97.50%, is considered the best-performing model. Importantly, our method only requires a modest quantity of training data to produce these outcomes. © 2025 ieee.

关键词： Ultrasonic imaging

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