检索结果-内蒙古大学图书馆

arXiv 2020年

作者： Cooke, Colin L. Kong, Fanjie Chaware, Amey Zhou, Kevin C. Kim, Kanghyun Xu, Rong Michael Ando, D. Yang, Samuel J. Konda, Pavan Chandra Horstmeyer, Roarke Duke University Electrical and Computer Engineering Department Duke University Biomedical Engineering Department Google Research Applied Science Team

This paper introduces a new method of data-driven microscope design for virtual fluorescence microscopy. Our results show that by including a model of illumination within the first layers of a deep convolutional neural network, it is possible to learn task-specific LED patterns that substantially improve the ability to infer fluorescence image information from unstained transmission microscopy images. We validated our method on two different experimental setups, with different magnifications and different sample types, to show a consistent improvement in performance as compared to conventional illumination methods. Additionally, to understand the importance of learned illumination on inference task, we varied the dynamic range of the fluorescent image targets (from one to seven bits), and showed that the margin of improvement for learned patterns increased with the information content of the target. This work demonstrates the power of programmable optical elements at enabling better machine learning algorithm performance and at providing physical insight into next generation of machine-controlled imaging systems. Copyright © 2020, The Authors. All rights reserved.

关键词： Fluorescence microscopy

来源：评论

学校读者我要写书评

暂无评论

Spectro-ViT: A Vision Transformer Model for GABA-edited MRS Reconstruction Using Spectrograms

arXiv

引用

arXiv 2023年

作者： Dias, Gabriel Berto, Rodrigo Pommot Oliveira, Mateus Ueda, Lucas Dertkigil, Sergio Costa, Paula D.P. Shamaei, Amirmohammad Souza, Roberto Harris, Ashley Rittner, Leticia School of Electrical and Computer Engineering University of Campinas Campinas Brazil Department of Biomedical Engineering University of Calgary Calgary Canada Hotchkiss Brain Institute University of Calgary Calgary Canada Alberta Children’s Hospital Research Institute Calgary Canada Research and Development Center in Telecommunications CPQD Campinas Brazil School of Medical Sciences University of Campinas Campinas Brazil Artificial Intelligence Lab. Recod.ai University of Campinas Campinas Brazil Department of Electrical and Software Engineering University of Calgary Calgary Canada Department of Radiology University of Calgary Calgary Canada ICT 352C 2500 University Dr NW CalgaryABT2N 1N4 Canada

Purpose: To investigate the use of a Vision Transformer (ViT) to reconstruct/denoise GABA-edited magnetic resonance spectroscopy (MRS) from a quarter of the typically acquired number of transients using spectrograms. Theory and Methods: A quarter of the typically acquired number of transients collected in GABA-edited MRS scans are pre-processed and converted to a spectrogram image representation using the Short-Time Fourier Transform (STFT). The image representation of the data allows the adaptation of a pre-trained ViT for reconstructing GABA-edited MRS spectra (Spectro-ViT). The Spectro-ViT is fine-tuned and then tested using in vivo GABA-edited MRS data. The Spectro-ViT performance is compared against other models in the literature using spectral quality metrics and estimated metabolite concentration values. Results: The Spectro-ViT model significantly outperformed all other models in four out of five quantitative metrics (mean squared error, shape score, GABA+/water fit error, and full width at half maximum). The metabolite concentrations estimated (GABA+/water, GABA+/Cr, and Glx/water) were consistent with the metabolite concentrations estimated using typical GABA-edited MRS scans reconstructed with the full amount of typically collected transients. Conclusion: The proposed Spectro-ViT model achieved state-of-the-art results in reconstructing GABA-edited MRS, and the results indicate these scans could be up to four times faster. © 2023, CC BY.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Preliminary analysis of the performance metrics for the 26 GHz band receiving channel of the snowbear project 8

Preliminary analysis of the performance metrics for the 26 G...

引用

8th ESA International Workshop on Tracking, Telemetry and Command Systems for Space Applications, TTC 2019

作者： Concaro, Filippo Marchetti, Matteo Pasian, Marco Darmstadt Germany University of Pavia Dept. of Electrical Computer and Biomedical Engineering Pavia Italy

ISBN: (纸本)9781728136998

Due to congestion in the Earth Exploration Service (EES) X-Band (8.0-8.4 GHz) and MetSat X-Band (7.75-7.9 GHz) used today by most Earth Observation satellites for payload data downlinks and the increase in required downlink data rates, ESA has embarked on the technology preparation for the exploitation of the 26 GHz band by future Earth Observation missions. The Agency will use this band operationally for the first time in a polar orbit mission for the EUMETSAT Metop-SG spacecrafts (first Launch in 2021), currently under development by ESA. In this paper the SNOWBEAR (Svalbard grouNd StatiOn for Wide Band Earth observation dAta Reception) project status and goals, together with the receiving ground station system are described. Data collection and analysis in terms of 'absolute' (i.e., signal strength, cross-polar level, tracking errors, signal to noise, number of recorded frames) and 'relative' (measured performances compared against theoretical ones) statistics are also introduced. Preliminary analysis of two orbit cycles (around 210 passes each) is then reported, to give a first insight of the link performance and to introduce problems and possible causes. © 2019 IEEE.

关键词： Orbits

来源：评论

学校读者我要写书评

暂无评论

System Model Extraction of MEMS Beam Resonator for Colpitts Crystal Oscillator

System Model Extraction of MEMS Beam Resonator for Colpitts ...

引用

International Conference on engineering and Emerging Technologies (ICEET)

作者： Faisal Nawaz Muhammad Sulaiman Umar Jamil Rana Iqtidar Shakoor Department of Electrical & Computer Engineering Air University Islamabad Pakistan Department of Mechatronics & Biomedical Engineering Air University Islamabad Pakistan

ISBN: (数字)9781728145815

ISBN: (纸本)9781728145822

A complementary metal oxide semiconductor-micro electro-mechanical systems (CMOS-MEMS) platform is applicable for integrating MEMS resonators and CMOS integrated circuits on a single chip. This provides a monolithic connection of MEMS with electronics. With this integration, different configurations of monolithically integrated MEMS resonators and CMOS amplifiers have been developed for commercial multi user purpose. It also provides variety of design flexibilities for resonator applications. In this paper, the design and analysis of a 2.14MHz MEMS beam resonator for Colpitts crystal oscillator circuit is presented. A MEMS beam resonator is designed to function as an oscillator. The proposed MEMSColpitts oscillator circuit can generate 1 to 5MHz clocks, when operated in different modes. This oscillator works specifically on 2.14MHz by macro model extraction for 9 th mode only. The beam resonator requires approximately 10V dc to operate. The actuation was simulated in IntelliSuite (thermo-electro mechanical module). A macro model of resonator is extracted by using system model extraction (SME) and utilized in electrical circuit of Colpitts crystal oscillator. The comparison with other research works is also presented.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Bus Authentication and Anti-Probing Architecture Extending Hardware Trusted Computing Base Off CPU Chips and Beyond

A Bus Authentication and Anti-Probing Architecture Extending...

引用

Annual International Symposium on computer Architecture, ISCA

作者： Zhenyu Xu Thomas Mauldin Zheyi Yao Shuyi Pei Tao Wei Qing Yang Department of Electrical Computer and Biomedical Engineering University of Rhode Island Kingston Rhode Island USA

ISBN: (数字)9781728146614

ISBN: (纸本)9781728146621

Tamper-proof hardware designs present a great challenge to computer architects. Most existing research limits hardware trusted computing base (TCB) to a CPU chip and anything off the CPU chip is vulnerable to probing and tampering. This paper introduces a new hardware design that provides strong defenses against physical attacks on interconnecting buses between chips in a computer system thereby extending the hardware TCB beyond CPU chips. The new approach is referred to as DIVOT: Detecting Impedance Variations Of Transmission-lines (Tx-lines). Every Tx-line in a computer system, such as a bus and interconnection wire has a unique, intrinsic, and fingerprint-like property: Impedance Inhomogeneity Pattern (IIP), i.e. the impedance distribution over distance. Such unpredictable, uncontrollable, and non-reproducible IIP fingerprints can be used to authenticate a Tx-line to ensure the confidentiality and integrity of data being transmitted. In addition, physical probes perturb the electromagnetic (EM) field around a Tx-line, leading to an altered IIP. As a result, runtime monitoring of IIPs can also be used to actively detect physical probing, snooping, and wire-tapping on buses. While the physics behind the IIP is known, the major technical breakthrough of DIVOT is the new integrated time domain reflectometer, iTDR, that is capable of carrying out in-situ and runtime monitoring of a Tx-line without interfering with normal data transfers. The iTDR is based on two innovations: analog-to-probability conversion (APC) and probability density modulation (PDM). The iTDR performs runtime IIP measurements noninvasively and is CMOS-compatible allowing it to be integrated with any interface logic connected to a bus. DIVOT is a generic, scalable, cost-effective, and low-overhead security solution for any computer system from servers to embedded computers in smart mobile devices and IoTs. To demonstrate the proposed architecture, a working prototype of DIVOT has been built on an FP

关键词：

来源：评论

学校读者我要写书评

暂无评论

Performance analysis of distributed intelligent reflecting surfaces for wireless communications

arXiv

引用

arXiv 2020年

作者： Galappaththige, Diluka Loku Kudathanthirige, Dhanushka Baduge, Gayan Amarasuriya Aruma School of Electrical Computer and Biomedical Engineering Southern Illinois University CarbondaleIL United States

In this paper, a comprehensive performance analysis of a distributed intelligent reflecting surfaces (IRSs)-aided communication system is presented. First, the optimal signal-to-noise ratio (SNR), which is attainable through the direct and reflected channels, is quantified by controlling the phase-shifts of the distributed IRSs. Next, this optimal SNR is statistically characterized by deriving tight approximations to the probability density function (PDF) and cumulative distribution function (CDF) for Nakagami-m fading. Our PDF/CDF analysis is used to derive tight approximations/bounds for the outage probability, achievable rate, and average symbol error rate (SER) in closed-form. To obtain useful insights, the asymptotic outage probability and average SER are derived for the high SNR regime. Thereby, the achievable diversity order and array gains are quantified. Our asymptotic performance analysis reveals that the diversity order can be boosted by using distributed passive IRSs without generating additional electromagnetic (EM) waves via active radio frequency chains. Our asymptotic rate analysis shows that the lower and upper rate bounds converge to an asymptotic limit in large reflecting element regime. Moreover, the transmission impairments are studied by investigating the detrimental effects of phaseshift quantization errors and the spatially correlated fading at the IRSs. Our analysis is validated via Monte-Carlo simulations. We present a rigorous set of numerical results to investigate the performance gains of the proposed system model. Our analytical and numerical results reveal that the performance of single-input single-output wireless systems can be boosted by recycling the EM waves generated by a transmitter through distributed passive IRS reflections to enable constructive signal combining at a receiver. © 2020, CC0.

关键词： Probability density function

来源：评论

学校读者我要写书评

暂无评论

Negative Label Guided Discriminative Canonical Correlation Analysis for Semi-Supervised and Semi-Paired Learning

Negative Label Guided Discriminative Canonical Correlation A...

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Xin Guo Song Wang Yun Tie Lin Qi Ling Guan School of Information Engineering Zhengzhou University Zhengzhou China Department of Electrical Computer and Biomedical Engineering Ryerson University Toronto Canada

ISBN: (数字)9781728133201

ISBN: (纸本)9781728133218

Semi-supervised learning is a popular trend for learning based methods in recent years, as it fully exploits both the labeled and unlabeled samples in a dataset. This paper sets itself apart from most existing semi-supervised learning algorithms, which only use the exact labels of data already known. We take the negative label as side information to guide the process of semi-supervised learning. Two types of supervision information are regarded as negative label; the first type indicates that a sample definitely does not belong to a specific category, and the second indicates that two samples come from different views, and cannot have a one to one correspondence. By reasonably assuming that nearby points should have similar class indicators, the data labels are propagated under the negative label and the geometric structure revealed by both labeled and unlabeled points. Specifically, we predict one to one pair information by utilizing the neighbor information of samples, under the guidance of the negative pair label. Extensive experiments on several datasets demonstrate the effectiveness of our proposed method.

关键词： Prediction algorithms Gold Semisupervised learning Cats Market research Training Machine learning

来源：评论

学校读者我要写书评

暂无评论

VOLUMETRIC LANDMARK DETECTION WITH A MULTI-SCALE SHIFT EQUIVARIANT NEURAL NETWORK

arXiv

引用

arXiv 2020年

作者： Ma, Tianyu Gupta, Ajay Sabuncu, Mert R. School of Electrical and Computer Engineering Meinig School of Biomedical Engineering Cornell University Department of Radiology Weill Cornell Medical College

Deep neural networks yield promising results in a wide range of computer vision applications, including landmark detection. A major challenge for accurate anatomical landmark detection in volumetric images such as clinical CT scans is that large-scale data often constrain the capacity of the employed neural network architecture due to GPU memory limitations, which in turn can limit the precision of the output. We propose a multi-scale, end-to-end deep learning method that achieves fast and memory-efficient landmark detection in 3D images. Our architecture consists of blocks of shift-equivariant networks, each of which performs landmark detection at a different spatial scale. These blocks are connected from coarse to fine-scale, with differentiable resampling layers, so that all levels can be trained together. We also present a noise injection strategy that increases the robustness of the model and allows us to quantify uncertainty at test time. We evaluate our method for carotid artery bifurcations detection on 263 CT volumes and achieve a better than state-of-the-art accuracy with mean Euclidean distance error of 2.81mm. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

GAN-Based Realistic Bone Ultrasound Image and Label Synthesis for Improved Segmentation 23rd

GAN-Based Realistic Bone Ultrasound Image and Label Synthesi...

引用

23rd International Conference on Medical Image Computing and computer-Assisted Intervention, MICCAI 2020

作者： Alsinan, Ahmed Z. Rule, Charles Vives, Michael Patel, Vishal M. Hacihaliloglu, Ilker Department of Electrical and Computer Engineering Rutgers University PiscatawayNJ United States Department of Computer Science Rutgers University PiscatawayNJ United States Department of Orthopedics Rutgers New Jersey Medical School NewarkNJ United States Department of Electrical and Computer Engineering Johns Hopkins University BaltimoreMD United States Department of Biomedical Engineering Rutgers University PiscatawayNJ United States Department of Radiology Rutgers University Robert Wood Johnson Medical School New BrunswickNJ United States

ISBN: (纸本)9783030597245

To provide a safe alternative, for intra-operative fluoroscopy, ultrasound (US) has been investigated as an alternative safe imaging modality for various computer assisted orthopedic surgery (CAOS) procedures. However, low signal to noise ratio, imaging artifacts and bone surfaces appearing several millimeters (mm) in thickness have hindered the wide spread application of US in CAOS. In order to provide a solution for these problems, research has focused on the development of accurate, robust and real-time bone segmentation methods. Most recently methods based on deep learning have shown very promising results. However, scarcity of bone US data introduces significant challenges when training deep learning models. In this work, we propose a computational method, based on a novel generative adversarial network (GAN) architecture, to (1) produce synthetic B-mode US images and (2) their corresponding segmented bone surface masks in real-time. We show how a duality concept can be implemented for such tasks. Armed by two convolutional blocks, referred to as self-projection and self-attention blocks, our proposed GAN model synthesizes realistic B-mode bone US image and segmented bone masks. Quantitative and qualitative evaluation studies are performed on 1235 scans collected from 27 subjects using two different US machines to show comparison results of our model against state-of-the-art GANs for the task of bone surface segmentation using U-net. © 2020, Springer Nature Switzerland AG.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Design and synthesis of an ultra wide band FSS for mm-wave application via general regression neural network and multiobjective bat algorithm

引用

Journal of Microwaves, Optoelectronics and Electromagnetic Applications 2019年第4期18卷 530-544页

作者： Neto, Miércio C.A. Araújo, Jasmine P.L. Mota, Raimundo J.S. Barros, Fabrício J.B. Ferreira, Flávio H.C.S. Cavalcante, Gervásio P.S. Castro, Bruno S.L. Institute of Technology Faculty of Electrical and Biomedical Engineering Federal University of Pará Brazil Faculty of Computer Science Castanhal University Campus Federal University of Pará Brazil

In this work is presented a hybrid bioinspired optimization technique that associates a General Regression Neural Network (GRNN) with the Multiobjective Bat Algorithm (MOBA), for the design and synthesis of the Frequency Selective Surfaces (FSS), aiming its application in data communication systems by diffusion of millimeter waves, specifically, in the IEEE 802.15.3c standard. The designed device consists of planar arrangements of metallizations (patches), diamond-shaped, arranged over a RO4003 substrate. The FSS proposed in this study presents an operation with ultra-wide band characteristics, its patch designed to cover the range of 40.0 GHz at 70.0 GHz, i.e., 30.0 GHz bandwidth and 60.0 GHz resonance. The upper and lower cutoff frequencies, referring to the transmission coefficient's scattering matrix (dB), were obtained at the cutoff threshold at -10dB, to control the bandwidth of the device. © 2019 SBMO/SBMag.

关键词： Regression analysis

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：