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2018 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)最新文献

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2018 IEEE International Work Conference on Bioinspired Intelligence 2018 IEEE仿生智能国际工作会议
Pub Date : 2018-07-01 DOI: 10.1109/iwobi.2018.8464189
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引用次数: 0
Pre-training Long Short-term Memory Neural Networks for Efficient Regression in Artificial Speech Postfiltering 基于预训练的长短期记忆神经网络在人工语音后滤波中的有效回归
Pub Date : 2018-07-01 DOI: 10.1109/IWOBI.2018.8464204
Marvin Coto-Jiménez
Several attempts to enhance statistical parametric speech synthesis have contemplated deep-learning-based postfil-ters, which learn to perform a mapping of the synthetic speech parameters to the natural ones, reducing the gap between them. In this paper, we introduce a new pre-training approach for neural networks, applied in LSTM-based postfilters for speech synthesis, with the objective of enhancing the quality of the synthesized speech in a more efficient manner. Our approach begins with an auto-regressive training of one LSTM network, whose is used as an initialization for postfilters based on a denoising autoencoder architecture. We show the advantages of this initialization on a set of multi-stream postfilters, which encompass a collection of denoising autoencoders for the set of MFCC and fundamental frequency parameters of the artificial voice. Results show that the initialization succeeds in lowering the training time of the LSTM networks and achieves better results in enhancing the statistical parametric speech in most cases, when compared to the common random-initialized approach of the networks.
一些增强统计参数语音合成的尝试已经考虑了基于深度学习的后滤波器,它学习将合成语音参数映射到自然语音参数,从而减少它们之间的差距。在本文中,我们介绍了一种新的神经网络预训练方法,应用于基于lstm的语音合成后滤波器,目的是以更有效的方式提高合成语音的质量。我们的方法从一个LSTM网络的自回归训练开始,它被用作基于去噪自编码器架构的后滤波器的初始化。我们在一组多流后滤波器上展示了这种初始化的优点,该后滤波器包含一组用于MFCC集和人工语音基频参数的去噪自编码器。结果表明,与常用的随机初始化方法相比,初始化方法可以有效地降低LSTM网络的训练时间,并且在大多数情况下在增强统计参数语音方面取得了更好的效果。
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引用次数: 3
M-Phase Feature Extraction Algorithm for Phenotype Classification from Cancer Brightfield Microscopy 肿瘤亮场显微镜表型分类的m相特征提取算法
Pub Date : 2018-07-01 DOI: 10.1109/IWOBI.2018.8464208
A. Mora-Zuniga, Steve Quiros-Barrantes, Francisco Siles
In this paper a workflow to extract cell features from brightfield microscopy image sequences is proposed. An event driven approach, combined with a forward and backward tracking limited by the cell's circularity was proven enough to extract relevant features that can be used to classify the cells into four phenotypes related to chemosensitivity studies: cell cycle arrest, apoptotic, damage proliferation and cells that have repaired their DNA damage. An average F1-Score greater than 0.7 was achieved in the detection and follow up of the events on images that present characteristics that impede the use of classic image segmentation and methods.
本文提出了一种从明场显微图像序列中提取细胞特征的工作流程。事件驱动的方法,结合受细胞圆周限制的向前和向后跟踪,已被证明足以提取相关特征,可用于将细胞分类为与化学敏感性研究相关的四种表型:细胞周期阻滞,凋亡,损伤增殖和修复其DNA损伤的细胞。对于图像上存在阻碍经典图像分割和方法使用的特征的事件的检测和跟踪,平均F1-Score大于0.7。
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引用次数: 1
Evaluation of Fog Reduction Algorithms for Photogrammetric Applications in Agriculture 农业摄影测量中的减雾算法评价
Pub Date : 2018-07-01 DOI: 10.1109/IWOBI.2018.8464186
L. Chavarría-Zamora, Sergio Arriola-Valverde, R. Rímolo-Donadío
Haze is a natural scaterring effect of light that can blur images, lowering their quality and difficulting the scene analysis. In this paper, several state-of-the-art dehazing algorithms are evaluated through a subjective method for image quality assesment. The Dark Channel Prior algorithm, which resulted the best option within the evaluated algorithms, was further optimized by manipulating color spaces before its application in order to achieve a better reconstruction of the images.
雾霾是一种自然散射光的效果,可以模糊图像,降低他们的质量和困难的场景分析。本文通过主观评价图像质量的方法对几种最先进的消雾算法进行了评价。暗通道先验算法在评估算法中得到最佳选择,在应用前通过操纵色彩空间进一步优化,以实现更好的图像重建。
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引用次数: 0
Automatic Classification of Normal and Abnormal PCG Recording Heart Sound Recording Using Fourier Transform 基于傅立叶变换的心音记录正常与异常PCG自动分类
Pub Date : 2018-07-01 DOI: 10.1109/IWOBI.2018.8464131
Anjali Yadav, M. Dutta, C. Travieso-González, J. B. Alonso
Cardiovascular diseases are very common these days and there arises a need for regular diagnosis of humans. Phonocardiogram is an effective diagnostic tool for analysing the heart sound. It helps in providing better information regarding clinical condition of the heart. This paper proposes an algorithmic method for differentiating a normal heart sound from an abnormal one using the PCG sound data. Cepstrum analysis has been performed on both types of signals and features are extracted from the heart sound. The extracted features are trained and tested with the help of a support vector machine classifier. The proposed method has achieved an accuracy of 95% in correctly classifying a heart sound PCG signal as normal and abnormal.
如今,心血管疾病非常普遍,因此需要对人类进行定期诊断。心音图是分析心音的有效诊断工具。它有助于提供关于心脏临床状况的更好的信息。本文提出了一种利用心电心电图数据区分正常心音和异常心音的算法。对这两种信号进行倒频谱分析,提取心音特征。在支持向量机分类器的帮助下,对提取的特征进行训练和测试。该方法对心音PCG信号进行正常和异常分类的准确率达到95%。
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引用次数: 9
Genome Copy Number Feature Selection Based on Chromosomal Regions Alterations and Chemosensitivity Subtypes 基于染色体区域改变和化学敏感性亚型的基因组拷贝数特征选择
Pub Date : 2018-07-01 DOI: 10.1109/IWOBI.2018.8464182
J. Vargas, R. Mora-Rodríguez, Francisco Siles
Cancer disease causes millions of deaths throughout the world and thousands in Costa Rica, and cancer treatment causes an immense economic burden on the social security system because drugs against the disease are extremely expensive. Through DNA sequencing techniques, the copy number of each gene could be found in order to describe how many times a gene is repeated within chromosomes. This type of data is of great importance since the cancer manifests a phenomenon called aneuploidy that consists of alterations in the number of chromosomes copies. Theories about the importance of aneuploidy in cancer supposed this phenomenon is a evolutionary engine that allows the disease to grow and resist changes produced by the organism and the treatments applied to these tissues. Studies have collected data on the number of copies in well-known databases such as CCLE and TCGA, which can be used to analyze the relationship between alterations in DNA and resistance to chemotherapies. In this study as a contribution, it was proposed to use statistical pattern recognition methods in order to identify chromosomal regions of DNA related to cancer chemosensitivity subtypes (resistant and sensitive subgroups) and then use these regions for CCLE cell lines labeling and TCGA samples classification.
癌症在全世界造成数百万人死亡,在哥斯达黎加造成数千人死亡,癌症治疗给社会保障系统带来了巨大的经济负担,因为治疗这种疾病的药物极其昂贵。通过DNA测序技术,可以找到每个基因的拷贝数,以描述一个基因在染色体内重复的次数。这种类型的数据非常重要,因为癌症表现出一种称为非整倍体的现象,由染色体拷贝数的改变组成。关于非整倍体在癌症中的重要性的理论认为,这种现象是一种进化引擎,它允许疾病生长并抵抗由生物体和应用于这些组织的治疗产生的变化。研究收集了诸如CCLE和TCGA等知名数据库中拷贝数的数据,这些数据可用于分析DNA改变与化疗耐药性之间的关系。本研究提出利用统计模式识别方法鉴定与癌症化学敏感性亚型(耐药亚群和敏感亚群)相关的DNA染色体区域,并利用这些区域进行CCLE细胞系标记和TCGA样本分类。
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引用次数: 1
Parallel Implementation in a GPU of the Calculation of Disparity Maps for Computer Vision 计算机视觉视差图计算的GPU并行实现
Pub Date : 2018-07-01 DOI: 10.1109/IWOBI.2018.8464217
Juan S. Ríos-Ramos, O. A. Nava, Hilda Maria Chable Martinez, Eduardo Rodríguez-Martínez
The high computational cost in computing disparity maps has relegated their use in real-time computer vision tasks. This work shows the design of a parallel algorithm for the generation of disparity maps which decreases the redundant operations during the stereo matching process. The proposed algorithm also uses a median filter to decrease the noise present in the generated disparity map, achieving an acceleration of 1135x on a GPU. In addition to the implementation of the parallel algorithm, GPU resources were used to improve memory access time and code optimization.
视差图的高计算成本降低了视差图在实时计算机视觉任务中的应用。本文设计了一种视差图的并行生成算法,减少了立体匹配过程中的冗余操作。该算法还使用中值滤波器来减少生成的视差图中存在的噪声,在GPU上实现了1135倍的加速。除了实现并行算法外,还利用GPU资源改进内存访问时间和代码优化。
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引用次数: 1
Preliminary Design Methodology and Prototype of a Passive Magnetic Suspension System for a Blood Axial Flow Pump 血轴流泵被动磁悬浮系统的初步设计方法及样机
Pub Date : 2018-07-01 DOI: 10.1109/IWOBI.2018.8464185
J. D. Zamora-Bolanos, M. Vílchez-Monge, Gabriela Ortiz-León, J. L. Crespo-Mariño
In Costa Rica, cardiovascular diseases are one of the principal death causes. At Instituto Tecnologico de Costa Rica there is a working group developing an axial ventricular assistance device. One of the problems that must be solved is the design of a system allowing the rotor to levitate within the device's channel, avoiding the impeller to cause any damage to the blood. This paper presents the design process for a passive magnetic suspension system prototype, based on the use of an external concentrator bearing, and an internal radial bearing.
在哥斯达黎加,心血管疾病是主要死亡原因之一。在哥斯达黎加理工学院,有一个工作组正在开发一种轴向心室辅助装置。必须解决的问题之一是设计一种系统,允许转子悬浮在设备的通道内,避免叶轮对血液造成任何损害。本文介绍了一种基于外部集中轴承和内部径向轴承的被动磁悬浮系统原型的设计过程。
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引用次数: 1
Deep Multi-class Eye Segmentation for Ocular Biometrics 眼部生物识别的深度多类眼睛分割
Pub Date : 2018-07-01 DOI: 10.1109/IWOBI.2018.8464133
Peter Rot, Ž. Emeršič, V. Štruc, P. Peer
Segmentation techniques for ocular biometrics typically focus on finding a single eye region in the input image at the time. Only limited work has been done on multi-class eye segmentation despite a number of obvious advantages. In this paper we address this gap and present a deep multi-class eye segmentation model build around the SegNet architecture. We train the model on a small dataset (of 120 samples) of eye images and observe it to generalize well to unseen images and to ensure highly accurate segmentation results. We evaluate the model on the Multi-Angle Sclera Database (MASD) dataset and describe comprehensive experiments focusing on: i) segmentation performance, ii) error analysis, iii) the sensitivity of the model to changes in view direction, and iv) comparisons with competing single-class techniques. Our results show that the proposed model is viable solution for multi-class eye segmentation suitable for recognition (multi-biometric) pipelines based on ocular characteristics.
眼部生物识别的分割技术通常侧重于在输入图像中找到单个眼睛区域。尽管多类别眼睛分割有许多明显的优势,但目前只做了有限的工作。在本文中,我们解决了这一差距,并提出了一个围绕SegNet架构构建的深度多类眼分割模型。我们在一个小的眼睛图像数据集(120个样本)上训练模型,并观察到它可以很好地推广到未见过的图像,并确保高度准确的分割结果。我们在多角度巩膜数据库(MASD)数据集上评估了该模型,并描述了综合实验,重点是:i)分割性能,ii)误差分析,iii)模型对视图方向变化的敏感性,以及iv)与竞争的单类技术的比较。结果表明,该模型适用于基于眼特征的多生物特征识别管道,是一种可行的多类眼分割解决方案。
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引用次数: 52
Cellular-Level Characterization of Dengue and Zika Virus Infection Using Multiagent Simulation 使用多agent模拟登革热和寨卡病毒感染的细胞水平表征
Pub Date : 2018-07-01 DOI: 10.1109/IWOBI.2018.8464219
A. Alvarado, Ricardo Corrales, Maria José Soares Leal, A. Ossa, R. Mora, Manuel Arroyo, Andrea Gomez, Alan Calderon, Jorge L. Arias-Arias
In this paper we present a computational model aimed at characterizing the Zika viral infection at a cellular level based on measurements done on viral Dulbecco plaques over time, and describe our current state of progress in the modeling task. So far we have developed an agent-based simulation model of the dispersion of the virus on the cells conforming the viral plaque. The growth rate of the viral plaques and the number of cells counted on each plaque were used to characterize the viral infection in terms of parameters related to the fate of infected cells, such as the probability of a cell infecting its neighboring cells and the probability of an infected cell of dying at any given moment. The model can be used to predict viral plaque growth patterns similar to those observed in the laboratory. Our current efforts focus on optimizing the model parameters to fit the experimental data. Further development of the model includes the description of viral infection kinetics of specific viral strains. Our model has been developed using the agent-based modeling language Netlogo [1].
在本文中,我们提出了一个计算模型,旨在基于对病毒Dulbecco斑块随时间的测量,在细胞水平上表征寨卡病毒感染,并描述了我们目前在建模任务中的进展状态。到目前为止,我们已经开发了一种基于代理的病毒在符合病毒斑块的细胞上分散的模拟模型。病毒斑块的生长速度和每个斑块上计数的细胞数量被用来根据与感染细胞命运相关的参数来表征病毒感染,例如细胞感染邻近细胞的概率和被感染细胞在任何给定时刻死亡的概率。该模型可用于预测类似于在实验室观察到的病毒斑块生长模式。我们目前的工作重点是优化模型参数以拟合实验数据。该模型的进一步发展包括对特定病毒株的病毒感染动力学的描述。我们的模型是使用基于代理的建模语言Netlogo[1]开发的。
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引用次数: 2
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2018 IEEE International Work Conference on Bioinspired Intelligence (IWOBI)
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