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SEGMENTATION OF A HIGH-RESOLUTION URBAN SCENE USING TEXTURE OPERATORS

computer VISION GRAPHICS AND IMAGE processing 1984年第3期25卷 273-310页

作者： CONNERS, RW TRIVEDI, MM HARLOW, CA Remote Sensing and Image Processing Laboratory Department of Electrical and Computer Engineering Louisiana State University Baton Rouge Louisiana 70803

A study aimed at segmenting a high-resolution black and white image of Sunnyvale, California, is described. In this study regions were classified as belonging to any one of nine classes: residential, commercial/industrial, mobile home, water, dry land, runway/taxiway, aircraft parking, multilane highway, and vehicle parking. The classes were selected so that they directly relate to the Defense Mapping Agency's Mapping, Charting and Geodesy tangible features. To attack the problem a statistical segmentation procedure was devised. The primitive operators used to drive the segmentation are texture measures derived from cooccurrence matrices. The segmentation procedure considers three kinds of regions at each level of the segmentation: uniform, boundary, and unspecified. At every level the procedure differentiates uniform regions from boundary and unspecified regions. In the assigns a class label to the uniform regions. The boundary and unspecified regions are split to form higher level regions. The methodologies involved are mathematically developed as a series of hypothesis tests. While only a one-level segmentation was performed studies are described which show the capabilities of each of these hypothesis tests. In particular an 83% correct classification was obtained in testing the labeling procedure. These studies indicate that the proposed procedure should be useful for land use classifications as well as other problems.

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Knowledge based unification of medical archives

Knowledge based unification of medical archives

引用

5th International Network Conference, INC 2005

作者： Diou, C. Falelakis, M. Delopoulos, A. Electrical and Computer Engineering Department Information Processing Laboratory Aristotle University of Thessaloniki Greece

ISBN: (纸本)9781841022727

In this paper, the structure of a system is proposed that aims at providing clinicians with easy-to-use, well structured and accurate medical information for support of diagnosis, treatment, medical research and education that will be automatically concentrated from multiple sources. The collection and processing of such information (even in its digital form) is not a straightforward task because of three main constraints: Disparity, dispersion and voluminosity. The proposed model attempts to overcome the aforementioned obstacles by exploiting emerging multimedia database technologies. The most important aspect of the proposed system is its capability to handle user's queries at a semantic level by referring to respective medical knowledge bases that encapsulate relevant medical expertise. Core components of the system are tools that help clinicians or researchers to perform effective content-based search and retrieval of medical information that matches their interests. © 2005 University of the Aegean and University of Plymouth.

关键词： Diagnosis

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HRSpecNET: A Deep Learning-Based High-Resolution Radar Micro-Doppler Signature Reconstruction for Improved HAR Classification

IEEE Transactions on Radar Systems

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IEEE Transactions on Radar Systems 2024年 2卷 484-497页

作者： Biswas, Sabyasachi Manavi Alam, Ahmed Gurbuz, Ali C. Mississippi State University Department of Electrical and Computer Engineering Information Processing and Sensing Laboratory StarkvilleMS39672 United States

Micro-Doppler signatures (mu -DSs) are widely used for human activity recognition (HAR) using radar. However, traditional methods for generating mu -DS, such as the short-time Fourier transform (STFT), suffer from limitations, such as the tradeoff between time and frequency resolution, noise sensitivity, and parameter calibration. To address these limitations, we propose a novel deep learning (DL)-based approach to reconstruct high-resolution mu -DS directly from a 1-D complex time-domain signal. Our DL architecture consists of an autoencoder (AE) block to improve signal-to-noise ratio (SNR), an STFT block to learn frequency transformations to generate pseudo spectrograms, and, finally, a U-Net block to reconstruct high-resolution spectrogram images. We evaluated our proposed architecture on both synthetic and real-world data. For synthetic data, we generated 1-D complex time-domain signals with multiple time-varying frequencies and evaluated and compared the ability of our network to generate high-resolution mu -DS and perform in different SNR levels. For real-world data, a challenging radar-based American Sign Language (ASL) dataset consisting of 100 words was used to evaluate the classification performance achieved using the mu -DS generated by the proposed approach. The results showed that the proposed approach outperforms the classification accuracy of traditional STFT-based mu -DS by 3.48%. Both synthetic and experimental mu -DSs show that the proposed approach learns to reconstruct higher resolution and sparser spectrograms. © 2023 IEEE.

关键词： Signal to noise ratio

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ANALYTICAL MODELING OF PLASMA IMMERSION ION-IMPLANTATION TARGET CURRENT USING THE SPICE CIRCUIT SIMULATOR

JOURNAL OF VACUUM SCIENCE & TECHNOLOGY B

引用

JOURNAL OF VACUUM SCIENCE & TECHNOLOGY B 1994年第2期12卷 833-837页

作者： EN, W CHEUNG, NW Plasma Assisted Materials Processing Laboratory Department of Electrical Engineering and Computer Sciences University of California Berkeley California 94720

Plasma immersion ion implantation applies a series of negative high-voltage pulses to a target immersed in a plasma. An analytical model of the currents and potentials induced before, during, and after the negative bias in a planar geometry is presented. The effect of multiple pulses on the results is also studied. The model determines the time-varying ion current, electron current, total current, total dose, and sheath thickness for a piecewise linear voltage pulse. The sheath collapse is found to be important for high repetition rate pulses. Implementation of the model is done in SPICE, a circuit simulator. Comparison with experimental data has demonstrated the accuracy of the model.

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Implementing real-time partitioned convolution algorithms on conventional operating systems

Implementing real-time partitioned convolution algorithms on...

引用

14th International Conference on Digital Audio Effects, DAFx 2011

作者： Battenberg, Eric Avižienis, Rimas Parallel Computing Laboratory Department of Electrical Engineering and Computer Science University of California Berkeley CA United States

ISBN: (纸本)9782954035109

We describe techniques for implementing real-time partitioned convolution algorithms on conventional operating systems using two different scheduling paradigms: time-distributed (cooperative) and multi-threaded (preemptive). We discuss the optimizations applied to both implementations and present measurements of their performance for a range of impulse response lengths on a recent high-end desktop machine. We find that while the time-distributed implementation is better suited for use as a plugin within a host audio application, the preemptive version was easier to implement and significantly outperforms the time-distributed version despite the overhead of frequent context switches.

关键词： Impulse response

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Social Energy:Mining Energy From the Society

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IEEE/CAA Journal of Automatica Sinica 2017年第3期4卷 466-482页

作者： Jun Jason Zhang David Wenzhong Gao Yingchen Zhang Xiao Wang Xiangyang Zhao Dongliang Duan Xiaoxiao Dai Jun Hao Fei-Yue Wang Department of Electrical and Computer Engineering Ritchie School of Engineering and Computer ScienceUniversity of Denver IEEE National Renewable Energy Laboratory Qingdao Academy of Intelligent Industries(QAII) QingdaoShandongChinaand SKL-MCCSCASIA School of Automation Science and Electrical Engineering Beihang University Department of Electrical and Computer Engineering College of Engineering and Applied ScienceUniversity of Wyoming State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences(SKL-MCCSCASIA) Research Center of Computational Experiments and Parallel Systems National University of Defense Technology

The inherent nature of energy,i.e.,physicality,sociality and informatization,implies the inevitable and intensive interaction between energy systems and social *** this perspective,we define "social energy" as a complex sociotechnical system of energy systems,social systems and the derived artificial virtual systems which characterize the intense intersystem and intra-system *** recent advancement in intelligent technology,including artificial intelligence and machine learning technologies,sensing and communication in Internet of Things technologies,and massive high performance computing and extreme-scale data analytics technologies,enables the possibility of substantial advancement in socio-technical system optimization,scheduling,control and *** this paper,we provide a discussion on the nature of energy,and then propose the concept and intention of social energy systems for electrical power.A general methodology of establishing and investigating social energy is proposed,which is based on the ACP approach,i.e., "artificial systems"(A), "computational experiments"(C) and "parallel execution"(P),and parallel system methodology.A case study on the University of Denver(DU) campus grid is provided and studied to demonstrate the social energy *** the concluding remarks,we discuss the technical pathway,in both social and nature sciences,to social energy,and our vision on its future.

关键词： ACP distribution locational marginal pricing intelligent operation in power systems parallel control parallel intelligence parallel management social energy socio-technical energy systems

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Pillow talks: Bits over communications in WLAN 2

Pillow talks: Bits over communications in WLAN

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2nd Workshop for Mobile Sensing, Computing and Communication, MSCC 2015

作者： Dong, Xuan Zhu, Chunsheng Lv, Shaohe Wang, Lei Wang, Xiaodong Leung, Victor C.M. National Laboratory of Parallel and Distributed Processing National University of Defense Technology United States Department of Electrical and Computer Engineering University of British Columbia Canada Department of Network Engineering Dalian University of Technology China

ISBN: (纸本)9781450335188

Improving the channel utilization is a significant issue to enhance the performance in WLAN. This paper presents, Pillow Talks MAC (PT-MAC), a novel spectrum sharing mechanism to create an extra channel (pt-channel) for client- to-client transmission in WLAN. Obviously, The basic chal- lenge in our proposal is how pt-channel works concurrently and transparently with AP transmissions. To address the issue, in PT-MAC, selected clients are allowed to contend for pt-channel during uplink transmissions and talk freely under the ongoing downlink transmissions. Based on ad- vanced physical techniques, pt-channel transmitter receives and forwards the AP signals simultaneously within OFDM cyclic prefix, resulting in mixed signals are overheard by re- ceiver in pt-channel. However, the mixed message can be re- covered by pt-decoding system. Simulations and analytical results show that, PT-MAC reuses the spectrum in WLAN and achieves a throughput gain as large as 92% with similar fairness, when the ratio of downlink traffic is about 80%. © 2015 ACM.

关键词： Wireless local area networks (WLAN)

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CV-SincNet: Learning Complex Sinc Filters From Raw Radar Data for Computationally Efficient Human Motion Recognition

IEEE Transactions on Radar Systems

引用

IEEE Transactions on Radar Systems 2023年 1卷 493-504页

作者： Biswas, Sabyasachi Ayna, Cemre Omer Gurbuz, Sevgi Z. Gurbuz, Ali C. Department of Electrical and Computer Engineering Information Processing and Sensing Laboratory Mississippi State University Mississippi StateMS39672 United States Department of Electrical and Computer Engineering The University of Alabama TuscaloosaAL35487 United States

The utilization of radio-frequency (RF) sensing in cyber-physical human systems, such as human-computer interfaces or smart environments, is an emerging application that requires real-time human motion recognition. However, current state-of-the-art radar-based recognition techniques rely on computing various RF data representations, such as range-Doppler or range-Angle maps, micro-Doppler signatures, or higher dimensional representations, which have great computational complexity. Consequently, classification of raw radar data has garnered increasing interest, while remaining limited in the accuracy that can be attained for recognition of even simple gross motor activities. To help address this challenge, this paper proposes a more interpretable complex-valued neural network design. Complex sinc filters are designed to learn frequency-based relationships directly from the complex raw radar data in the initial layer of the proposed model. The complex-valued sinc layer consists of windowed band-pass filters that learn the center frequency and bandwidth of each filter. A challenging RF dataset consisting of 100 words from American Sign Language (ASL) is selected to verify the model. About 40% improvement in classification accuracy was achieved over the application of a 1D CNN on raw RF data, while 8% improvement was achieved compared to real-valued SincNet. Our proposed approach achieved a 4% improvement in accuracy over that attained with a 2D CNN applied to micro-Doppler spectrograms, while also reducing the overall computational latency by 71%. © 2023 IEEE.

关键词： Bandpass filters

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Lossless coding and visualization of 3-D medical images with lossy preview capability

Bioimaging

引用

Bioimaging 1996年第1期4卷 1-5页

作者： Sahinoglou, Haris Malassiotis, Sotiris Strintzis, Michael G. Information Processing Laboratory Department of Electrical and Computer Engineering University of Thessaloniki Thessaloniki 540 06 Greece

In this paper a combination of lossless and lossy compression techniques is presented for the storage and transmission of 3-D medical images. The lossy version of the data is used for fast preview when browsing through large databases. When only a small region is of interest then the lossless corrections for this region are transmitted. A special structuring of the bit-stream is also adopted to allow visualization directly from the compressed bit-stream.

关键词： 3-D medical images Transmission Visualization

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Local spectrum sensing in non-gaussian noise

Local spectrum sensing in non-gaussian noise

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2010 17th International Conference on Telecommunications, ICT 2010

作者： Zahabi, Sayed Jalal Tadaion, Ali A. Department of Electrical and Computer Engineering Statistical Signal Processing Laboratory Yazd University Yazd Iran

ISBN: (纸本)9781424452477

This paper deals with the local spectrum sensing problem in non-Gaussian noise. It is of great importance to reliably detect the presence of licensed users in cognitive radio. This task highly depends on the noise distribution, thus it is important to characterize the noise behavior as best as possible. Although Gaussian assumption for noise is of interest due to many reasons, it sometimes fails to model the behavior of noise in practice. In this paper we present a local spectrum sensing scheme in a broad family of non-Gaussian noise. We reasonably assume that the Primary User (PU) signal is Phase Shift Keying (PSK) modulated, where the number of constellation points, M, and the symbol code sequence are unknown to the Secondary Users (SU), as in practice. We also assume that the SUs are unaware of the PU signal complex amplitude and the non- Gaussian noise variance. Within this framework, we obtain the Generalized Likelihood Ratio Test (GLRT) as our spectrum sensing scheme and propose an approximate implementation of the resulting GLRT. Simulation results show that our proposed scheme has an acceptable performance. © 2009 IEEE.

关键词： Cognitive radio

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