The proceedings contain 27 papers. The topics discussed include: cognitively inspired artificial bipedal humanoid gait generation;personal identification using forearm vein patterns;k-same-net: neural-network-based fa...
ISBN:
(纸本)9781538608500
The proceedings contain 27 papers. The topics discussed include: cognitively inspired artificial bipedal humanoid gait generation;personal identification using forearm vein patterns;k-same-net: neural-network-based face deidentification;articulation acoustic kinematics in ALS speech: a longitudinal study case;voice pathology detection using deep learning: a preliminary study;analysis of disfluencies for automatic detection of mild cognitive impartment: a deep learning approach;automatic imageprocessing based dental image analysis using automatic Gaussian fitting energy and level sets;automatic event handling during robot assisted eye surgery;automatic identification of botanical samples of leaves using computer vision;approach of kinematic control for a nonholonomic wheeled robot using artificial neural networks and genetic algorithms;impact of target variable distribution type over the regression analysis in wind turbine data;image reconstruction of the human forearm by electrical impedance tomography;assessment of the spectral quality of fused images using the CIEDE2000 distance;a superpixel-based approach based on consensus for delineating agricultural plots;automated segmentation of powdery mildew disease from cherry leaves using imageprocessing;and control architecture to reproduce the knee and ankle movement using a transfemoral prosthesis.
Advances in wireless communication, digital systems and micro-electronic-mechanical system technologies led to the development of wireless sensor networks (WSNs) which are used in various critical real-world applicati...
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ISBN:
(纸本)9781538621295
Advances in wireless communication, digital systems and micro-electronic-mechanical system technologies led to the development of wireless sensor networks (WSNs) which are used in various critical real-world applications. The fact that WSNs are low cost and eliminate the need for infrastructure led to their replacing traditional networks in area/event monitoring and tracking applications. WSNs consist of small and resource-limited sensor nodes, due to which several problems arise in the WSN development process. One of these problems is coverage. Providing the best coverage with a minimum number of sensor nodes is an NP-hard problem known as the maximum coverage sensor deployment problem (MCSDP). Genetic algorithms (GAs) have been proved effective in solving optimization problems in many different disciplines (increasing coverage in WSNs, imageprocessing, route planning, etc.). In this study, a GPU-based parallel GA solution for increasing the coverage of a given homogeneous WSN topology in a 2-D Euclidean area is proposed which is the first time this technique is used and parallelized on GPUs to the best of our knowledge. Finally, performance results of the proposed algorithm are compared to the previous work with the emphasis on the achieved performance improvement.
As a kind of traditional Chinese Medicine,plaster has been favored by more and more patients because of its unique advantages in the treatment of *** the coating of plaster,its quality is very important to the ***,coa...
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ISBN:
(纸本)9781538631089;9781538631072
As a kind of traditional Chinese Medicine,plaster has been favored by more and more patients because of its unique advantages in the treatment of *** the coating of plaster,its quality is very important to the ***,coating surface defect detection is very *** current mainstream detection method is manual inspection,there are many disadvantages in this,such as extremely low efficiency and bad for *** light of this situation,a set of plaster coating quality automatic detection system based on machine vision has been proposed in this *** a detailed analysis of the coating defects,a set of image detection algorithms have been *** can be found from the experimental results that the algorithm can identify the type of defects and locate the position *** error detection rate is low,and the robustness is good.
Efficient solutions must be considered, in order to solve the problem of intensive computing of the imageprocessing applications and to achieve high real-time performance. The graphics processing unit (GPU) is an eff...
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We present an algorithm for creating high resolution anatomically plausible images consistent with acquired clinical brain MRI scans with large inter-slice spacing. Although large databases of clinical images contain ...
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ISBN:
(数字)9783319590509
ISBN:
(纸本)9783319590509;9783319590493
We present an algorithm for creating high resolution anatomically plausible images consistent with acquired clinical brain MRI scans with large inter-slice spacing. Although large databases of clinical images contain a wealth of information, medical acquisition constraints result in sparse scans that miss much of the anatomy. These characteristics often render computational analysis impractical as standard processingalgorithms tend to fail when applied to such images. Highly specialized or application-specific algorithms that explicitly handle sparse slice spacing do not generalize well across problem domains. In contrast, our goal is to enable application of existing algorithms that were originally developed for high resolution research scans to significantly undersampled scans. We introduce a model that captures fine-scale anatomical similarity across subjects in clinical image collections and use it to fill in the missing data in scans with large slice spacing. Our experimental results demonstrate that the proposed method outperforms current upsampling methods and promises to facilitate subsequent analysis not previously possible with scans of this quality.
Smart vision systems on a chip are promising for embedded applications. Currently, flexibility in the choice of integrated pre-processing tools is obtained at the expense of total silicon area and fill factor, which a...
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Brain tumors constitute one of the deadliest forms of cancers, with a high mortality rate. Of these, Glioblastoma multiforme (GBM) remains the most common and lethal primary brain tumor in adults. Tumor biopsy being c...
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ISBN:
(纸本)9781509060344
Brain tumors constitute one of the deadliest forms of cancers, with a high mortality rate. Of these, Glioblastoma multiforme (GBM) remains the most common and lethal primary brain tumor in adults. Tumor biopsy being challenging for brain tumor patients, noninvasive techniques like imaging play an important role in the process of brain cancer detection, diagnosis and prognosis;particularly using Magnetic Resonance Imaging (MRI). Therefore, development of advanced extraction and selection strategies of quantitative MRI features become necessary for noninvasively predicting and grading the tumors. In this paper we extract 56 three-dimensional quantitative MRI features, related to tumor image intensities, shape and texture, from 254 brain tumor patients. An adaptive neuro-fuzzy classifier based on linguistic hedges (ANFC-LH) is developed to simultaneously select significant features and predict the tumor grade. ANFC-LH achieves a significantly higher testing accuracy (85.83%) as compared to existing standard classifiers.
The proceedings contain 220 papers. The topics discussed include: intelligent disaster warning and response system with dynamic route selection for evacuation;leveraging cell phones for surveillance;using natural lang...
ISBN:
(纸本)9781538619599
The proceedings contain 220 papers. The topics discussed include: intelligent disaster warning and response system with dynamic route selection for evacuation;leveraging cell phones for surveillance;using natural language processing for analyzing Arabic poetry rhyme;artificial intelligence and sensors based assistive system for the visually impaired people;single image super resolution: an efficient approach using auto-learning and filter pooling;essential pre-processing tasks involved in data preparation for social network user behavior analysis;energy performance of optimally inclined free standing photovoltaic system;micro controller based automatic aquaphonic system using solar;performance comparison of DTN multicasting routing algorithms- opportunities and challenges;smooth video streaming in bandwidth fluctuating environment;survivable fiber optic networks design by using digital signal levels approach;and automation of home appliances using visible light communication.
This article addresses the study of the anomaly and fraud detection problem in the data from social services. The problem of detecting anomalies is extremely relevant for data-driven processes in the digital economy. ...
This article addresses the study of the anomaly and fraud detection problem in the data from social services. The problem of detecting anomalies is extremely relevant for data-driven processes in the digital economy. In this paper, we propose a two-step approach for the detection of anomalies using auto-encoders and the conjugacy indicator. An experimental study of the efficiency of the proposed algorithms was conducted using open-access data set.
Lensless imaging systems have the potential to provide new capabilities for lower size and weight configuration than traditional imaging systems. Lensless imagers frequently utilize computational imaging techniques, w...
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ISBN:
(纸本)9781510609457;9781510609464
Lensless imaging systems have the potential to provide new capabilities for lower size and weight configuration than traditional imaging systems. Lensless imagers frequently utilize computational imaging techniques, which moves the complexity of the system away from optical subcomponents and into a calibration process whereby the measurement matrix is estimated. We report on the design, simulation, and prototyping of a lensless imaging system that utilizes a 3D printed optically transparent random scattering element. Development of end-to-end system simulations, which includes simulations of the calibration process, as well as the data processing algorithm used to generate an image from the raw data are presented. These simulations utilize GPU-based raytracing software, and parallelized minimization algorithms to bring complete system simulation times down to the order of seconds. Hardware prototype results are presented, and practical lessons such as the effect of sensor noise on reconstructed image quality are discussed. System performance metrics are proposed and evaluated to discuss image quality in a manner that is relatable to traditional image quality metrics. Various hardware instantiations are discussed.
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