23 research outputs found

    A Survey on Design Methodologies for Accelerating Deep Learning on Heterogeneous Architectures

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    In recent years, the field of Deep Learning has seen many disruptive and impactful advancements. Given the increasing complexity of deep neural networks, the need for efficient hardware accelerators has become more and more pressing to design heterogeneous HPC platforms. The design of Deep Learning accelerators requires a multidisciplinary approach, combining expertise from several areas, spanning from computer architecture to approximate computing, computational models, and machine learning algorithms. Several methodologies and tools have been proposed to design accelerators for Deep Learning, including hardware-software co-design approaches, high-level synthesis methods, specific customized compilers, and methodologies for design space exploration, modeling, and simulation. These methodologies aim to maximize the exploitable parallelism and minimize data movement to achieve high performance and energy efficiency. This survey provides a holistic review of the most influential design methodologies and EDA tools proposed in recent years to implement Deep Learning accelerators, offering the reader a wide perspective in this rapidly evolving field. In particular, this work complements the previous survey proposed by the same authors in [203], which focuses on Deep Learning hardware accelerators for heterogeneous HPC platforms

    Automatic Vessel Segmentation in Wide-field Retina Images of Infants with Retinopathy of Prematurity

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    The earliest signs of Retinopathy of Prematurity (ROP) are tortuosity and dilation of retinal vessels. Such vascular changes are considered of primary importance for the diagnosis and the follow-up of the disease. However, a widely accepted computerized system for their quantitative measurement is still missing. Images taken from a preterm baby's eye are often low-contrast, noisy, and blurred. Algorithms that have been successfully applied to analyze adult retinal images do not work well in ROP images. We propose here a novel method for the automatic extraction of vessel centerline in wide-field ROP retinal images, based on a sparse tracking scheme. After a set of seed points is identified all over the image, vessels are traced by connecting those seeds by means of minimum cost paths, whose weights depend on similarity features and alignment evaluated by a custom line operator. The performance of the method was assessed on a dataset of 20 images acquired with the RetCam fundus camera. A sensitivity of 0.78 and a false detection rate of 0.15 were obtained with respect to manual ground truth reference

    Environmental and Pathogenic Factors Inducing Brown Apical Necrosis on Fruit of English (Persian) Walnut

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    Brown apical necrosis (BAN) is a most recently described disease affecting English (Persian) walnut fruit. BAN was only recorded in intensively managed walnut orchards and was found to be a disease complex mainly caused by Fusarium species. All fungi associated with this disease are polyphagous and ubiquitous, not specific to walnut. Consequently, BAN occurrence is more strictly dependent, than generally, on the interaction between pathological features and environmental conditions. Environmental variables identified with regression analysis showed that maximum temperature, angle of main wind direction versus tree row orientation, and orchard distance to the closest river/canal, all representative of climatic conditions occurring in the orchard, were related to fruit drop. The factor displaying the highest influence on severity of BAN fruit drop was maximum temperature and only subordinately factors are associated with relative humidity. BAN symptoms were reproduced with in planta artificial inoculation, and fruit drop of symptomatic fruit was significantly higher than that of the noninoculated trees for each type of inoculum (Fusarium semitectum, F. graminearum, and Alternaria spp.). F. semitectum and F. graminearum were more aggressive than Alternaria species, and the earliest artificial inoculations in mid-May resulted in the highest fruit drop. The extension of walnut fruit susceptibility and the conducive environmental factors to BAN are discussed
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