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International conference on Computer Communications and Electronics (Comptelix)

作者： Sharma, Vivek Sharma, Bharat Bhushan Nath, Ravinder Natl Inst Technol Hamirpur India

ISBN: (纸本)9781509047086

In present work, secure communication scheme for digital images based on discrete time unknown input observer (UIO) design blended with discrete time chaotic encryption is presented. Chaotic signals are pseudo random signals with no periodicity over infinite length. However, the series can be generated with the precise knowledge of the few parameters like system parameters and initial conditions of the chaotic system. With the given nature of pseudo-randomness and extreme sensitivity to parameters, chaotic sequences are ideal for encryption. In literature, these chaotic sequences are generally generated using continuous time chaotic systems. Since image data to be transmitted is in digital form and encryption algorithms are also executed on digital devices, so it is proposed to use discrete time chaotic communication scheme. Further, its effectiveness for encryption of digital images is also analyzed. To further enhance the security encrypted data is embedded in the dynamics of discrete time chaotic transmitter system. To recover the message at the receiver, design of discrete time UIO along with a procedure to recover unknown message signal using estimated states is given. Existence conditions for the UIO are analytically derived in terms of LMIs. Solution of these LMIs gives the observer design matrices. Robustness of UIO based chaotic communication scheme against attacks is analyzed by studying return maps of the transmitted signal. It is reported that security of chaotic communication scheme can be compromised by studying the return maps of the transmitted signal. To validate the proposed approach results of simulation and security analysis are presented.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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Blur vs. Block: Investigating the Effectiveness of Privacy-Enhancing Obfuscation for images 30

Blur vs. Block: Investigating the Effectiveness of Privacy-E...

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30th IEEE/CVF conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Li, Yifang Vishwamitra, Nishant Knijnenburg, Bart P. Hu, Hongxin Caine, Kelly Clemson Univ Clemson SC 29631 USA

ISBN: (纸本)9781538607336

Computer vision can lead to privacy issues such as unauthorized disclosure of private information and identity theft, but it may also be used to preserve user privacy. For example, using computer vision, we may be able to identify sensitive elements of an image and obfuscate those elements thereby protecting private information or identity. However, there is a lack of research investigating the effectiveness of applying obfuscation techniques to parts of images as a privacy-enhancing technology. In particular, we know very little about how well obfuscation works for human viewers or users' attitudes towards using these mechanisms. In this paper, we report results from an online experiment with 53 participants that investigates the effectiveness two exemplar obfuscation techniques: "blurring" and "blocking", and explores users' perceptions of these obfuscations in terms of image satisfaction, information sufficiency, enjoyment, and social presence. Results show that although "blocking" is more effective at de-identification compared to "blurring" or leaving the image "as is", users' attitudes towards "blocking" are the most negative, which creates a conflict between privacy protection and users' experience. Future work should explore alternative obfuscation techniques that could protect users' privacy and also provide a good viewing experience.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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Automated vehicle counting using image processing and machine learning

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SPIE conference on Health Monitoring of Structural and Biological systems

作者： Meany, Sean Eskew, Edward Martinez-Castro, Rosana Jang, Shinae Univ Connecticut Dept Civil & Environm Engn 261 Glenbrook Rd Storrs CT 06269 USA

ISBN: (数字)9781510608269

ISBN: (纸本)9781510608252;9781510608269

Vehicle counting is used by the government to improve roadways and the flow of traffic, and by private businesses for purposes such as determining the value of locating a new store in an area. A vehicle count can be performed manually or automatically. Manual counting requires an individual to be on-site and tally the traffic electronically or by hand. However, this can lead to miscounts due to factors such as human error A common form of automatic counting involves pneumatic tubes, but pneumatic tubes disrupt traffic during installation and removal, and can be damaged by passing vehicles. Vehicle counting can also be performed via the use of a camera at the count site recording video of the traffic, with counting being performed manually post-recording or using automatic algorithms. This paper presents a low-cost procedure to perform automatic vehicle counting using remote video cameras with an automatic counting algorithm. The procedure would utilize a Raspberry Pi micro-computer to detect when a car is in a lane, and generate an accurate count of vehicle movements. The method utilized in this paper would use background subtraction to process the images and a machine learning algorithm to provide the count. This method avoids fatigue issues that are encountered in manual video counting and prevents the disruption of roadways that occurs when installing pneumatic tubes.

关键词： Vehicle Counting Machine Learning image processing Wireless Sensor Network Raspberry Pi Wolfram

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Automatically Diagnosing HER2 Amplification Status for Breast Cancer Patients Using Large FISH images 25

Automatically Diagnosing HER2 Amplification Status for Breas...

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25th Signal processing and Communications Applications conference (SIU)

作者： Razavi, Salar Hatipoglu, Gokhan Yalcin, Hulya Istanbul Tech Univ Elect & Telecommun Engn Dept Visual Intelligence Lab Istanbul Turkey Virasoft Yazilim Istanbul Turkey

ISBN: (纸本)9781509064946

Fluorescence in situ hybridization (FISH) is a technique that prepares acceptable results for molecular imaging biomarkers to precisely and dependably detect and diagnose disorders which are sign of cancers. Since contemporary manual FISH signal analysis is low-effective and inconsistent, it is an attractive research area to develop automated FISH image scanning systems and computer-aided diagnosis (CAD) schemes. The gene expression of epidermal growth factor receptors 2 (HER2) is highly related to results of patients with probable breast cancer. Although FISH technology outperforms other methods, yet it has so many drawbacks. Traditional approaches on FISH analysis are performed manually by clinician. This lets the results are highly dependent to human eye. Also FISH test colors constitutes of dark blue and black regions, it is reasonable that human eye will fail to distinguish between colors. Therefore, the success of computer vision algorithms compared to human eye in analyzing gene expression rate in FISH images will be discussed in this study. Another objective of this study is to expand a CAD program to evaluate HER2 status using acquired images that have MIRAX format. Different large FISH images were chosen for this study from pathology laboratory from Acibadem Maslak hospital. The proposed CAD scheme first applies pre-processing median and gaussian filters. An adaptive thresholding method followed by a watershed segmentation algorithm is employed to segment cells of interest areas. Furthermore, analyzable cells are found and non detectable cells because of cell overlapping or image staining are discarded. The scheme then splits the detected analyzable region of interest into two red and green color spaces which is also followed by application of a scanning algorithm to detect the CEP17 green and HER2/neu red FISH signals separately. Finally, the proposed method calculates the ratio between independent green and red FISH signals of all analyzable cells identi

关键词： Breast Cancer Medical diagnostic imaging Fluorescent in situ hybridization (FISH) image HER2 testing

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Acceleration of calculations using block algorithms for the difference solution of the heat equation

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Journal of Physics: conference Series 2019年第5期1368卷

作者： D L Golovashkin L V Yablokova I D Reznik Image Processing Systems Institute of RAS - Branch of the FSRC 'Crystallography and Photonics' RAS Molodogvardejskaya street 151 Samara Russia 443001 Samara National Research University Moskovskoe Shosse 34 Samara Russia 443086

In this paper, we propose taking into account the architectural features of the processor at the stage of constructing the numerical method itself. This idea is illustrated by the example of the synthesis of a new difference scheme for the heat conduction equation, which has traditionally been the object of testing innovations in the theory of difference schemes. The architectural feature hierarchical structure of the computer memory chosen led to considerable communication costs even when a single hardware computational flow was used for organising the calculations. This feature is accounted for in computational linear algebra by using block algorithms, and in the theory of difference schemes, by using the technique of programming 'tiling'. However, for the two-layer difference schemes of block algorithms for solving grid equations, prior to the proposed work, it was not known because of the impossibility of organising block calculations by using the existing schemes. Here, we propose a new method of constructing two-layer difference schemes and a mixed scheme with a shift as an example of the application of this method. In the course of the experiments, a five-fold acceleration of calculations according to this scheme was demonstrated relative to the traditional explicit model, with the same computational complexity.

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Overlapping Community Detection with Seed Set Expansion by Local Cluster Coefficient 4

Overlapping Community Detection with Seed Set Expansion by L...

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IEEE International conference on Consumer Electronics - Taiwan (ICCE-TW)

作者： Su, Yi-Jen Lee, Che-Chun Shu Te Univ Dept Comp Sci & Informat Technol Kaohsiung Taiwan

ISBN: (纸本)9781509040179

Since Web 2.0 be announced, social media services become popular in these years. Due to multiple relationships existing simultaneously among the members of the community in real world, to detect all overlapping communities from complex networks is becoming an important issue. The paper proposed a novel overlapping community detection method by seed set expansion with local cluster coefficient (LCC). In addition, the detection result will be evaluated by measuring the cohesion quality of communities.

关键词： image edge detection Complex networks Facebook Clustering algorithms Internet conferences

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Enhancing JFCS Software with a New Mapping Module. Filling the Semantic Gap from Pixels to Meaningful Fuzzy Colors

Enhancing JFCS Software with a New Mapping Module. Filling t...

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IEEE International conference on Fuzzy systems (FUZZ-IEEE)

作者： Soto-Hidalgo, J. M. Martinez-Jimenez, P. M. Chamorro-Martinez, J. Sanchez, D. Univ Cordoba Dept Comp Architecture Elect & Elect Technol Cordoba Spain Univ Granada Dept Comp Sci & Artificial Intelligence Granada Spain

ISBN: (纸本)9781509060344

This paper introduces a new way of interaction in JFCS Software where users can view and navigate easily between different combinations of fuzzy colors and pixels in images. Fuzzy colors allow introducing semantics in the description of color by using linguistic labels, filling the semantic gap between the color representation in computers and the subjective human perception. JFCS (Java Fuzzy Color Space) Software, an open source (GPLv3) software with a user-friendly interface, provides an easy framework to design and automatically obtain customized fuzzy color spaces on the basis of an approach proposed by the authors in previous work. This new functionality in JFCS endows it with a very useful tool to visually analyze correspondences between pixels and fuzzy colors in images. Users can obtain combined mapped images where regions, corresponding to a combination of color concepts, are highlighted. In addition, users can describe and interact, in a simple and visual way, with colors present on a given image in terms of fuzzy colors.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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Learning To Score Olympic Events 30

Learning To Score Olympic Events

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30th IEEE/CVF conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Parmar, Paritosh Morris, Brendan Tran Univ Nevada Las Vegas NV 89154 USA

ISBN: (纸本)9781538607336

Estimating action quality, the process of assigning a "score" to the execution of an action, is crucial in areas such as sports and health care. Unlike action recognition, which has millions of examples to learn from, the action quality datasets that are currently available are small - typically comprised of only a few hundred samples. This work presents three frameworks for evaluating Olympic sports which utilize spatiotemporal features learned using 3D convolutional neural networks (C3D) and perform score regression with i) SVR, ii) LSTM, and iii) LSTM followed by SVR. An efficient training mechanism for the limited data scenarios is presented for clip-based training with LSTM. The proposed systems show significant improvement over existing quality assessment approaches on the task of predicting scores of Olympic events {diving, vault, figure skating}. While the SVR-based frameworks yield better results, LSTM-based frameworks are more natural for describing an action and can be used for improvement feedback.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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ASePPI: Robust Privacy Protection against De-Anonymization attacks 30

ASePPI: Robust Privacy Protection against De-Anonymization a...

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30th IEEE/CVF conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Ruchaud, Natacha Dugelay, Jean-Luc Eurecom 450 Route Chappes Sophia Antipolis France

ISBN: (纸本)9781538607336

The evolution of the video surveillance systems generates questions concerning protection of individual privacy. In this paper, we design ASePPI, an Adaptive Scrambling enabling Privacy Protection and Intelligibility method operating in the H.264/AVC stream with the aim to be robust against de-anonymization attacks targeting the restoration of the original image and the re-identification of people. The proposed approach automatically adapts the level of protection according to the resolution of the region of interest. Compared to existing methods, our framework provides a better trade-off between the privacy protection and the visibility of the scene with robustness against de-anonymization attacks. Moreover, the impact on the source coding stream is negligible.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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ACM International conference Proceeding Series

ACM International Conference Proceeding Series

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9th International conference on Signal processing systems, ICSPS 2017

ISBN: (纸本)9781450353847

The proceedings contain 43 papers. The topics discussed include: compressive sensing based interference cancellation for ultra dense network;performance analysis of computer virus detection from binary code using ensemble classifier;balance between performance and security in IPI-based key schemes using heartbeats;research for building high performance communication service based on Netty protocol in smart health;hybrid scheme to solve finite precision in digital chaotic random number generator;maximum likelihood indoor localization of a WiFi radio transmitter with structural knowledge;SAAP: a state-aware adaptive prediction strategy for CPU load of desktops;deep Q-learning to preserve connectivity in multi-robot systems;nature as a source for inspiring new optimization algorithms;structural damage detection of a concrete based on the autoregressive all-pole model parameters and artificial intelligence techniques;fire boundary detection method using a unique structure from motion for non-rigid bodies algorithm (SFM-NRBA);brightness preserving satellite image contrast enhancement using bacterial foraging algorithm;generalized multi-Bernoulli filters for track-before-detect of objects from image observations;amalgamation of video description and multiple object localization using single deep learning model;and time-domain processing for exact background clutter extraction and reduction in RCS measurement.

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