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IEEE International Symposium on Information Theory (ISIT)

作者： Javanmard, Adel Montanari, Andrea Stanford Univ Dept Elect Engn Stanford CA 94305 USA

ISBN: (纸本)9781457705953

We consider the problem of positioning a cloud of points in the Euclidean space R-d, using noisy measurements of a subset of pairwise distances. This task has applications in various areas, such as sensor network localizations, NMR spectroscopy of proteins, and molecular conformation. Also, it is closely related to dimensionality reduction problems and manifold learning, where the goal is to learn the underlying global geometry of a data set using measured local (or partial) metric information. Here we propose a reconstruction algorithm based on a semidefinite programming approach. For a random geometric graph model and uniformly bounded noise, we provide a precise characterization of the algorithm's performance: In the noiseless case, we find a radius r(0) beyond which the algorithm reconstructs the exact positions (up to rigid transformations). In the presence of noise, we obtain upper and lower bounds on the reconstruction error that match up to a factor that depends only on the dimension d, and the average degree of the nodes in the graph.

关键词： Eigenvalues and eigenfunctions Euclidean space Laplace equations Noise Noise measurement Programming Stress Symmetric matrices dimensionality reduction problems distance measurement geometry graph theory incomplete noisy distance measurements learning (artificial intelligence) manifold learning mathematical programming molecular conformation pairwise distances protein NMR spectroscopy random geometric graph model reconstruction algorithm semidefinite programming approach sensor network localizations uniformly bounded noise

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Validation of a Self-developed algorithm for Solving Inverse Problems on Resistance Networks 21

Validation of a Self-developed Algorithm for Solving Inverse...

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21st IEEE International Symposium on Computational Intelligence and Informatics

作者： Vizvari, Zoltan Gyorfi, Nina Klincsik, Mihaly Sari, Zoltan Toth, Attila Odry, Peter Univ Pecs Inst Engn & Smart Technol Dept Environm Engn Fac Engn & Informat Technol Pecs Hungary Univ Pecs Szentagothai Res Ctr Pecs Hungary Univ Pecs Fac Engn & Informat Technol Dept Tech Informat Inst Informat & Elect Technol Pecs Hungary Univ Pecs Fac Med Dept Physiol Pecs Hungary Univ Dunaujvaros Dept Comp Syst & Control Engn Inst Informat Technol Dunaujvaros Hungary

ISBN: (纸本)9781665426848

Due to its non-destructive nature, research of Electrical Impedance Tomography (EIT) is still receiving a great deal of attention in many areas of application. The advantage of the method over density-based methods (e. g. acoustic, optical measurements, etc.) is that it also allows to deduce the chemical properties of the examined material. In this article, our research group examines a new approach on the implementation of the method. Consequently, by modeling the studied material, which can be considered as a continuum, as a linear network with concentrated parameters, we would like to determine the weights on the branches of the graph, i.e. the resistances in our article. After defining the mathematical model, we created a physical model in order to validate the self-developed algorithm. We used a precision measurement procedure to calculate the resistance values placed on the branches of the graph.

关键词： Electrical Impedance Tomography reconstruction algorithm Validation of resistance network Inverse problem

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Real-time System for Short- and Long-Term Prediction of Vehicle Flow

Real-time System for Short- and Long-Term Prediction of Vehi...

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IEEE International Conference on Smart Data Services (SMDS)

作者： Bilotta, Stefano Nesi, Paolo Paoli, Irene Univ Florence Dept Informat Engn DISIT Lab Florence Italy

ISBN: (纸本)9781728187778

Nowadays, traffic management and sustainable mobility are becoming one of the central topics for intelligent transportation systems (ITS). Thanks to the today's technologies, it is possible to collect real-time data to monitor the traffic situation in some specific areas. An important challenge in ITS is the ability to predict road traffic variables. The short-term predictions of traffic aspects are a complex nonlinear task that has been the subject of many research efforts in the past few decades. Accessing to precise traffic flow data is mandatory for a large number of applications which have to guarantee high level of services such as: traffic flow reconstruction, which in turn is used to perform what-if analysis, conditioned routing, etc. They have to be reliable and precise for sending rescue teams and fire brigades. This paper proposes a solution for a short- and long-term traffic flow prediction estimation by using and comparing a number of machine learning approaches. The solution has been developed in the context of Sii-Mobility smart city mobility and transport national project and it is in use in other EC projects and solution such as Snap4City PCP EC and TRAFAIR CEF, but also for REPLICATE 112020 SCC1 and control room in Florence area.

关键词： smart city traffic sensors short-term predictions prediction models machine learning reconstruction algorithm traffic flow

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An approach for sensing underwater particles using digital holographic imaging

An approach for sensing underwater particles using digital h...

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Conference on Ocean Optics and Information Technology / International Symposium on Optoelectronic Technology and Application (OTA)

作者： Liu, Chao Wang, Xiaoping Hu, Yingtian Tang, Ming Shi, Zheng Zhejiang Univ Coll Opt Sci & Engn State Key Lab Modern Opt Instrumentat Hangzhou 310027 Zhejiang Peoples R China Zhejiang Univ Key Lab Ocean Observat Imaging Testbed Zhoushan 316021 Peoples R China

ISBN: (数字)9781510623439

ISBN: (纸本)9781510623439

The purpose of this paper is to use digital holographic imaging to capture the hologram of the underwater particles. Digital holography includes two steps: wavefront recording and wavefront reconstruction. In the experiments of the underwater particles, some technique issues, such as the principle of digital holography, zero-order item suppressing and reconstruction algorithm are discussed. The complex amplitude of the underwater particles is reconstructed using numerical methods based on the Kirchhoff-Fresnel integral formula. In this case, it enables reconstruction of the object wavefield in a plane at a distance d from hologram. This novel method for imaging the underwater particles using digital holography is an extremely valuable technique for the study of underwater particles fields as it has many advantages such as large depth of field, no focusing, high resolution and has the ability to record the wavefront information of all particles in the entire volume. Finally, this paper demonstrates it is possible for digital holographic imaging setup with less complexity to image underwater particles according to our laboratory results.

关键词： digital holography underwater particles reconstruction algorithm wavefront recording

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Acoustic Tomography for Detecting a Hot Spot in Grain Bulk

Acoustic Tomography for Detecting a Hot Spot in Grain Bulk

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International Conference on Measuring Technology and Mechatronics Automation

作者： Yan, Hua Cui, Ke Xin Liu, Li Jun Qi, Yue Shenyang Univ Technol Sch Informat Sci & Engn Shenyang Peoples R China Hunan Univ Changsha Peoples R China

ISBN: (纸本)9780769535838

A hot spot is a localized high temperature zone in a grain bulk and normally spoilage begins in this location. Acoustic temperature tomography for detecting a hot spot in grain bulk is investigated. The region monitored is assumed to be square and divided into 400 pixels. 16 sound sources/receivers are set on its periphery. An acoustic temperature field reconstruction algorithm based on inverse multiquadrics approximation and truncated singular value decomposition is proposed. Using this algorithm, 400 temperature field models with a hot spot positioned at the midpoint of each pixel in turn have been reconstructed from exact or perturbed time-of-flight data. reconstruction results indicate that the algorithm proposed is good at reconstructing hot spot temperature, especially at reconstructing hot spot position. Thus it is expected to be used in detecting hot spots in grain bulk.

关键词： acoustic tomography reconstruction algorithm hot spot detection temperature measurement stored grain

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Comparison of Image Quality and Quantification Parameters between *** and OSEM reconstruction Methods on FDG-PET/CT Images in Patients with Metastatic Breast Cancer

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JOURNAL OF IMAGING 2023年第3期9卷 65-65页

作者： Naghavi-Behzad, Mohammad Vogsen, Marianne Gerke, Oke Dahlsgaard-Wallenius, Sara Elisabeth Nissen, Henriette Juel Jakobsen, Nick Moldrup Braad, Poul-Erik Vilstrup, Mie Holm Deak, Paul Hildebrandt, Malene Grubbe Andersen, Thomas Lund Univ Southern Denmark Dept Clin Res DK-5000 Odense Denmark Odense Univ Hosp Dept Nucl Med DK-5000 Odense Denmark Odense Univ Hosp Ctr Personalized Response Monitoring Oncol DK-5000 Odense Denmark Odense Univ Hosp Dept Oncol DK-5000 Odense Denmark Reg Southern Denmark Dept Clin Engn DK-6200 Aabenraa Denmark Healthcare Sci Technol GE Healthcare Chicago IL USA Odense Univ Hosp Ctr Innovat Med Technol DK-5000 Odense Denmark Rigshosp Dept Clin Physiol & Nucl Med DK-2100 Copenhagen Denmark

We compared the image quality and quantification parameters through bayesian penalized likelihood reconstruction algorithm (***) and ordered subset expectation maximization (OSEM) algorithm for 2-[F-18]FDG-PET/CT scans performed for response monitoring in patients with metastatic breast cancer in prospective setting. We included 37 metastatic breast cancer patients diagnosed and monitored with 2-[F-18]FDG-PET/CT at Odense University Hospital (Denmark). A total of 100 scans were analyzed blinded toward *** and OSEM reconstruction algorithms regarding image quality parameters (noise, sharpness, contrast, diagnostic confidence, artefacts, and blotchy appearance) using a five-point scale. The hottest lesion was selected in scans with measurable disease, considering the same volume of interest in both reconstruction methods. SULpeak (g/mL) and SUVmax (g/mL) were compared for the same hottest lesion. There was no significant difference regarding noise, diagnostic confidence, and artefacts within reconstruction methods;*** had significantly better sharpness (p < 0.001) and contrast (p = 0.001) than the OSEM reconstruction, while the OSEM reconstruction had significantly less blotchy appearance compared with *** reconstruction (p < 0.001). Quantitative analysis on 75/100 scans indicated that *** reconstruction had significantly higher SULpeak (5.33 +/- 2.8 vs. 4.85 +/- 2.5, p < 0.001) and SUVmax (8.27 +/- 4.8 vs. 6.90 +/- 3.8, p < 0.001) compared with OSEM reconstruction. In conclusion, *** reconstruction revealed better sharpness, better contrast, higher SUVmax, and higher SULpeak, while OSEM reconstruction had less blotchy appearance.

关键词： reconstruction algorithm FDG-PET CT metastatic breast cancer Q Clear

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Adaptive Low Power Detection of Sparse Events in Wireless Sensor Networks

Adaptive Low Power Detection of Sparse Events in Wireless Se...

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IEEE Wireless Communications and Networking Conference (WCNC)

作者： Alwakeel, Ahmed S. Abdelkader, Mohamed F. Seddik, Karim G. Ghuniem, Atef Sinai Univ Dept Commun & Elect Cairo Egypt Port Said Univ Dept Elect Engn Port Fouad Egypt Amer Univ Cairo Dept Elect Engn Cairo Egypt

ISBN: (纸本)9781479930838

Compressive Sensing (CS) has recently opened the door for efficient algorithms to solve various data gathering problems. Among these problems is sparse events detection in wireless sensor networks. In this problem, it is desirable to reduce the sensing cost by minimizing the number of sensors and the amount of data sent by each sensor. In this paper, we model the problem of sparse event detection as a compressive support recovery problem. We exploit the sparse and the binary nature of the event signal in the reconstruction algorithm using sequential compressive sensing. This provides an efficient solution to the problem, even under the assumptions of wide sensing area and high levels of noise. Simulation results show an improved performance under different compression ratios as compared to previous CS based approaches. It also shows the robustness of the proposed approach at low SNRs.

关键词： compressed sensing signal detection signal reconstruction wireless sensor networks CS SNR adaptive low power detection data gathering problems reconstruction algorithm sensing cost reduction sequential compressive sensing sparse event detection wide sensing area Compressed sensing Event detection Mathematical model Sensors Signal to noise ratio Vectors

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SINGLE-SHOT MULTISPECTRAL IMAGE ACQUISITION FOR LOW-ALTITUDE REMOTE SENSING USING LIGHT DIFFRACTION TECHNIQUES 10

SINGLE-SHOT MULTISPECTRAL IMAGE ACQUISITION FOR LOW-ALTITUDE...

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10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)

作者： Iturrino, Carlos Arias, Fernando X. Sierra, Heidy Arzuaga, Emmanuel Univ Puerto Rico Lab Appl Remote Sensing Imaging & Photon Mayaguez PR 00682 USA Univ Puerto Rico Dept Elect & Comp Engn Mayaguez PR 00682 USA Univ Puerto Rico Dept Comp Sci & Engn Mayaguez PR USA

ISBN: (纸本)9781728152943

Multispectral imaging devices currently being used in a variety of applications typically follow opto-mechanical designs. These designs often present the disadvantage of a bulky and heavy construction, limiting their applicability in new lowaltitude remote sensing applications deployed on acquisition systems with constrained weight and dimension requirements. This paper presents the design and construction of a simple optical system based on a transmission grating and a lightweight commercial camera for snapshot multispectral image acquisition. The system can be mounted on a small drone for low-altitude aerial remote sensing, and is capable of separating the spectral information from the spatial scene and generating multispectral HD images and 4K videos. In addition, we propose a fast algorithm for recovering multispectral scenes from their respective acquired spectral projections. Experimental results show similarity of the compared waveforms, and that the maximum peak of the reconstructed wavelength varies up to 13nm from reference spectroradiometer data.

关键词： Multispectral Imaging Adaptive Optics Relay Lens Transmission Grating Drone reconstruction algorithm Convolution

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Snapshot Hyperspectral Light Field Imaging 30

Snapshot Hyperspectral Light Field Imaging

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30th IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Xiong, Zhiwei Wang, Lizhi Li, Huiqun Liu, Dong Wu, Feng Univ Sci & Technol China Hefei Anhui Peoples R China Beijing Inst Technol Beijing Peoples R China

ISBN: (纸本)9781538604571

This paper presents the first snapshot hyperspectral light field imager in practice. Specifically, we design a novel hybrid camera system to obtain two complementary measurements that sample the angular and spectral dimensions respectively. To recover the full 5D hyperspectral light field from severely undersampled measurements, we then propose an efficient computational reconstruction algorithm by exploiting the large correlations across the angular and spectral dimensions through self-learned dictionaries. Simulation on an elaborate hyperspectral light field dataset validates the effectiveness of the proposed approach. Hardware experimental results demonstrate that, for the first time to our knowledge, a 5D hyperspectral light field containing 9 x 9 angular views and 27 spectral bands can be acquired in a single shot.

关键词： Angle Light fields single-shot reconstruction algorithm Snapshots Demand Driven Direct Digital Dissemination

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FBP and the interior problem in 2D tomography

FBP and the interior problem in 2D tomography

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IEEE Nuclear Science Symposium/Medical Imaging Conference (NSS/MIC)/18th International Workshop on Room-Temperature Semiconductor X-Ray and Gamma-Ray Detectors

作者： Bilgot, Anne Desbat, Laurent Perrier, Valerie UJF Grenoble 1 CNRS TIMC IMAG UMR 5525 F-38041 Grenoble France Grenoble INP CNRS TIMC F-38041 Grenoble France

ISBN: (纸本)9781467301206

We consider the Filtered Back Projection reconstruction method in the case of interior data in Computerized Tomography. In this framework we prove that the difference between the FBP reconstruction and the measured function is a continuous function. This demonstrates that the FBP reconstruction contains the discontinuities of the measured image. Thus FBP can be considered as a local reconstruction method in CT. We show numerical experiments on both simulated and real data.

关键词： X-Ray Computed Tomography reconstruction algorithm Tomography discontinuities backprojection observational data Continuous Function

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