We present an algorithm for structured prediction under online bandit feedback. The learner repeatedly predicts a sequence of actions, generating a structured output. It then observes feedback for that output and no o...
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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 paper presents an attention-based model for end-to-end Chinese image text recognition. The proposed model includes an encoder and a decoder. For each input text image, the encoder part firstly combines deep convo...
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ISBN:
(纸本)9783319700908;9783319700892
This paper presents an attention-based model for end-to-end Chinese image text recognition. The proposed model includes an encoder and a decoder. For each input text image, the encoder part firstly combines deep convolutional layers with bidirectional Recurrent Neural Network to generate an ordered, high-level feature sequence, which could avoid the complicated text segmentation pre-processing. Then in the decoder, a recurrent network with attention mechanism is developed to generate text line output, enabling the model to selectively exploit image features from the encoder correspondingly. The whole segmentation-free model allows end-to-end training within a standard backpropagation algorithm. Extensive experiments demonstrate significant performance improvements comparing to baseline systems. Furthermore, qualitative analysis reveals that the proposed model could learn the alignment between input and output in accordance with the intuition.
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.
A new technique of Mueller-matrix mapping of polycrystalline structure of histological sections of biological tissues is suggested. The algorithms of reconstruction of distribution of parameters of linear and circular...
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ISBN:
(数字)9781510612501
ISBN:
(纸本)9781510612501;9781510612495
A new technique of Mueller-matrix mapping of polycrystalline structure of histological sections of biological tissues is suggested. The algorithms of reconstruction of distribution of parameters of linear and circular birefringence of prostate histological sections are found. The interconnections between such distributions and parameters of linear and circular birefringence of prostate tissue histological sections are defined. The comparative investigations of coordinate distributions of phase anisotropy parameters formed by fibrillar networks of prostate tissues of different pathological states (adenoma and carcinoma) are performed. The values and ranges of change of the statistical (moments of the 1st - 4th order) parameters of coordinate distributions of the value of linear and circular birefringence are defined. The objective criteria of cause of Benign and malignant conditions differentiation are determined.
Underwater images are known to be strongly deteriorated by a combination of wavelength-dependent light attenuation and scattering. This results in complex color casts that depend both on the scene depth map and on the...
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ISBN:
(纸本)9781538607336
Underwater images are known to be strongly deteriorated by a combination of wavelength-dependent light attenuation and scattering. This results in complex color casts that depend both on the scene depth map and on the light spectrum. Color transfer, which is a technique of choice to counterbalance color casts, assumes stationary casts, defined by global parameters, and is therefore not directly applicable to the locally variable color casts encountered in underwater scenarios. To fill this gap, this paper introduces an original fusion-based strategy to exploit color transfer while tuning the color correction locally, as a function of the light attenuation level estimated from the red channel. The Dark Channel Prior (DCP) [16] is then used to restore the color compensated image, by inverting the simplified Koschmieder light transmission model, as for outdoor dehazing. Our technique enhances image contrast in a quite effective manner and also supports accurate transmission map estimation. Our extensive experiments also show that our color correction strongly improves the effectiveness of local keypoints matching(1).
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