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

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VL-ICOON: integration of iconographical databases of the built heritage

VL-ICOON: integration of iconographical databases of the bui...

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international conference on Virtual systems and MultiMedia

作者： I. Bertels K. Van Balen D. Kinnaes G. Venkatasubban J. Rademakers R. Lemaire Centre of Conservation Katholieke Universiteit Leuven Belgium Libis-net Katholieke Universiteit Leuven Belgium

This paper presents the VL-ICOON project, a research project focussing on the Integration of Iconographical Databases of the Built Heritage. Part of the paper deals with the development of the VL-ICOON database as a case study on making iconographical documentation of Built Heritage more easily accessible by using international standards, guidelines and new technologies. Further we focus on the technical requirements and developments for exchanging information of this kind between different partners through the internet. Accessibility to such intelligent image based information can be of great interest for conservators, heritage managers or other end users served with virtual representations of the built heritage.

关键词： Protection Software libraries Documentation Standards development internet Informatics image databases Guidelines Paper technology Collaboration

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Improved modified fast Haar Wavelet transformation [MFHWT] based visible watermarking

Improved modified fast Haar Wavelet transformation [MFHWT] b...

引用

international conference on Computing and Networking technology (ICCNT)

作者： Shefaly Sharma Jaspreet Kaur Shipra Gupta Computer science and Engineering Lovely Professional University Phagwara Punjab

ISBN: (纸本)9781479939275

With the explosive growth of internet technology, many innovative applications requiring exchange of large amount of data have become feasible and hence security of data have become a critical issue. In this paper, a robust and secure visible image watermarking algorithm is purposed. This purposed algorithm is based on Multi Wavelets with Modified fast Haar Wavelet transform [MFHWT]. MFHWT is the latest technique used for wavelets transformation which is used to perform image analysis at faster rate than previous techniques. The main idea of the purposed algorithm is to decompose the original image into fine scale sub bands using MFHWT according to the size of the Watermark. In this algorithm, the obtained watermarked image. In this algorithm has very high Peak signal to Noise Ratio [PSNR].

关键词： Watermarking Wavelet transforms PSNR Robustness image coding Algorithm design and analysis

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A novel image rejection CMOS mixer using T-structure filter

A novel image rejection CMOS mixer using T-structure filter

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IEEE international Caracas conference on Devices, Circuits and systems

作者： Anh-Tuan Phan Chang-Wan Kim Min-Suk Kang Mun-Suk Chong Sang-Gug Lee Chun-Deok Su RFME Laboratory Information and Communications University Daejeon South Korea Samsung Advanced Institute of Technology Suwon South Korea

ISBN: (纸本)0780387775

In this paper, an image rejection mixer in heterodyne architecture for 2 GHz band applications based on 0.18 /spl mu/m CMOS technology is presented. The designed mixer uses a T-structure filter to suppress the image signal, leading to the improvements in the noise figure (NF) and conversion gain. An image rejection of 25-85 dB is obtained in a 150 MHz of bandwidth from 1.95 to 2.1GHz with IF varying from 200 to 350MHz. The simulation results show single-side band (SSB) NF of 5 dB improved by 3.4 dB, the conversion gain of 10.5 dB, improved by more than 3 dB. The circuit operates at the supply voltage of 1.8 V, and dissipates 12 mW.

关键词： Filters CMOS technology Noise measurement image converters signal design Noise figure Bandwidth Circuit simulation Amplitude modulation Gain

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16th IFIP WG 12.5 international conference on Artificial Intelligence Applications and Innovations, AIAI 2020

16th IFIP WG 12.5 International Conference on Artificial Int...

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16th IFIP WG 12.5 international conference on Artificial Intelligence Applications and Innovations, AIAI 2020

ISBN: (纸本)9783030491857

The proceedings contain 75 papers. The special focus in this conference is on Artificial Intelligence Applications and Innovations. The topics include: Using Multimodal Contextual Process Information for the Supervised Detection of Connector Lock Events;a Machine Learning Model to Detect Speech and Reading Pathologies;Forecasting Hazard Level of Air Pollutants Using LSTM’s;hypotheses Tests Using Non-asymptotic Fuzzy Estimators and Fuzzy Critical Values;preservation of the Exchange Principle via Lattice Operations on (S,N)– Implications;Versatile internet of Things for Agriculture: An eXplainable AI Approach;Acoustic Resonance Testing of Glass IV Bottles;AI based Real-Time signal Reconstruction for Wind Farm with SCADA Sensor Failure;Autonomous Navigation for Drone Swarms in GPS-Denied Environments Using Structured Learning;Trustworthy AI Needs Unbiased Dictators!;chemical Laboratories 4.0: A Two-Stage Machine Learning System for Predicting the Arrival of Samples;predicting Physical Properties of Woven Fabrics via Automated Machine Learning and Textile Design and Finishing Features;real-Time Surf Manoeuvres’ Detection Using Smartphones’ Inertial Sensors;SDN-Enabled IoT Anomaly Detection Using Ensemble Learning;harnessing Social Interactions on Twitter for Smart Transportation Using Machine Learning;an Intelligent Cloud-based Platform for Effective Monitoring of Patients with Psychotic Disorders;applying Deep Learning to Predicting Dementia and Mild Cognitive Impairment;Bridging the Gap Between AI and Healthcare Sides: Towards Developing Clinically Relevant AI-Powered Diagnosis systems;know Yourself: An Adaptive Causal Network Model for Therapeutic Intervention for Regaining Cognitive Control;multi-omics Data and Analytics Integration in Ovarian Cancer;An Introduction of FD-Complete Constraints;overlap-based Undersampling Method for Classification of Imbalanced Medical Datasets;greek Lyrics Generation.

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Indexing and searching distributed image library

Indexing and searching distributed image library

引用

IEEE international conference on systems, Man and Cybernetics

作者： J. You W.P. Zhu J. Liu School of Computing and Information Griffith University Brisbane QLD Australia School of Information Technology University of Queensland QLD Australia Department of Computing Hong Kong Polytechnic University Hong Kong China

The internet and wireless communication offer unprecedented access to information. To effectively collect useful information from massive available sources requires the development of new methodologies and techniques that can substantially increase speed and flexibility in a distributed environment. Focusing on content-based image retrieval, this paper presents the use of transportable agents as the steering tool for dynamic indexing and flexible searching.

关键词： Indexing Libraries image retrieval Content based retrieval Distributed computing Portable computers Information retrieval Search engines Concurrent computing Embedded computing

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Single image Dehazing Through Feed Forward Artificial Neural Network 3rd

Single Image Dehazing Through Feed Forward Artificial Neural...

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3rd EAI international conference on Cognitive Computing and Cyber Physical systems, IC4S 2022

作者： Sharmila, K. Soni Asha, A.V.S. Archana, P. Chandra, K. Ramesh Department of CSE Shri Vishnu Engineering College for Women Bhimavaram India Department of ECE Vishnu Institute of Technology Bhimavaram India

ISBN: (纸本)9783031289743

Due to light scattering by air particles, images taken under bad lighting conditions (such as haze, fog, mist, or smog) have a reduced level of visibility. One blurry image can be made visible again using single image dehazing techniques. Due to the ill-posedness of the Single image dehazing problem, it is difficult to solve. Even though, the Dark channel prior (DCP) has been the most prevalent method for image dehazing algorithms, but it suffers from huge computational time and picture quality. The accurate transmission map estimation is one of the best preferred ways to achieve the least computational time and high picture quality in DCP. Hence, this work is focused on constructing transmission map of a hazy image based on feed forward artificial neural network. The recommended method uses a feed forward ANN to conduct the transmission map straight from the minimum channel and a normalizing procedure to increase the re-covered image information. With a training set of eighty images, the network is trained by means of mean square error (MSE). The proposed method utilizing peak signal to noise ratio (PSNR) and structural similarity (SSIM) index measures are used to assess the restoration quality. The investigational conclusions have demonstrated that, the suggested method outperforms the dehazing of an input image without degrading visible quality (PSNR = 69.16, SSIM index = 0.8913). In addition, the proposed method is suited for real-time applications given the average computing time it achieves is 1.03 s. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Restoration

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Semantic image Retrieval Using Collaborative Indexing and Filtering

Semantic Image Retrieval Using Collaborative Indexing and Fi...

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IEEE WIC ACM international conference on Web Intelligence (WI)

作者： C.H.C. Leung Yuanxi Li Computer Science Department Hong Kong Baptist University Hong Kong China

With the rapid development of multimedia technology, web images have become increasingly available and it constitutes a significant component of multimedia contents on the internet. Since Web images can be represented in various formats and dimensions, searching such information are far more challenging than text-based search. While some basic forms of image retrieval are available on the internet, these tend to be inflexible and have significant limitations. Currently, most of these image retrieval systems only rely on shallow image information (e.g., text annotation, metadata, color, etc.). Here, we present an approach for deep concept-based image retrieval, which focuses on high-level human perception, incorporating subtle nuances and emotional impressions on the images. We also propose a user-interactive and innovative adaptive method for image search that overcomes the current limitations.

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LEARNING SPARSE DICTIONARIES WITH A POPULARITY-based MODEL

LEARNING SPARSE DICTIONARIES WITH A POPULARITY-BASED MODEL

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IEEE international conference on Acoustics, Speech and signal Processing

作者： Jianzhou Feng Li Song Xiaoming Huo Xiaokang Yang Wenjun Zhang Institute of Image Communication & Information Proc. Shanghai Jiaotong University Shanghai China School of Industrial and Systems Engineering Georgia Institute of Technology Atlanta USA

Sparse signal representation based on overcomplete dictionaries has recently been extensively investigated, rendering the state-of-the-art results in signal, image and video processing. We propose a novel dictionary learning algorithm--the PK-SVD algorithm--which assumes prior probabilities on the dictionary atoms and learns a sparse dictionary under a popularity-based model. The prior distribution brings the flexibility that is desirable in applications. We examine our algorithm in both synthetic tests and image denoising experiments.

关键词： Dictionaries Noise level Matching pursuit algorithms Encoding Sparse matrices image denoising Noise reduction

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An Iris Recognition System Using Phase-based image Matching

An Iris Recognition System Using Phase-Based Image Matching

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IEEE international conference on image Processing

作者： Kazuyuki Miyazawa Koichi Ito Takafumi Aoki Koji Kobayashi Atsushi Katsumata Graduate School of Information Sciences Tohoku University Sendai Japan Yamatake Corporation Higashi-shinagawa Japan Graduate School of Information Sciences University of Tohoku Sendai Japan

This paper presents an implementation of iris recognition algorithm using phase-based image matching-an image matching technique using phase components in 2D discrete Fourier transforms (DFTs) of given images. Our experimental observation clearly shows that the use of phase components of iris images makes possible to achieve highly accurate iris recognition even for low-quality iris images. In this paper, we consider the problem of designing a compact phase-based iris recognition algorithm especially suitable for hardware implementation. We also present prototype implementation of an iris recognition system based on the proposed algorithm. The prototype system fully utilizes state-of-the-art DSP (digital signal processor) technology to achieve real-time iris recognition capability within a compact hardware module.

关键词： Iris recognition image matching signal processing algorithms Hardware Prototypes Discrete Fourier transforms Algorithm design and analysis Digital signal processing Digital signal processors Real time systems

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Performance evaluation and comparison of modified denoising method and the local adaptive wavelet image denoising method

Performance evaluation and comparison of modified denoising ...

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international conference on Intelligent systems and signal Processing (ISSP)

作者： Jignasa M. Parmar S. A. Patil Department of Electronics and Telecommunication R. C. Patel Institute of Technology Dist-Dhule MS India

ISBN: (纸本)9781479903160

Removal of noise is an important step in the image restoration process, but denoising of image remains a challenging problem in recent research associate with image processing. Denoising is used to remove the noise from corrupted image, while retaining the edges and other detailed features as much as possible. This noise gets introduced during acquisition, transmission & reception and storage & retrieval processes. In this paper, to find out denoised image the modified denoising method and the local adaptive wavelet image denoising method can be used. The noisy image is denoised by modified denoising method which is based on wavelet domain and spatial domain and the local adaptive wavelet image denoising method which is based on wavelet domain. In this paper, we have evaluated and compared performances of modified denoising method and the local adaptive wavelet image denoising method. These methods are compared with other based on PSNR (Peak signal to noise ratio) between original image and noisy image and PSNR between original image and denoised image. Simulation and experiment results for an image demonstrate that RMSE of the local adaptive wavelet image denoising method is least as compare to modified denoising method and the PSNR of the local adaptive wavelet image denoising method is high than other method. Therefore, the image after denoising has a better visual effect. In this paper, these two methods are implemented by using MATLAB for denoising of image.

关键词： Wiener filters Wavelet transforms image denoising Wavelet domain PSNR

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