1,720,987 research outputs found
Deep Skin Detection on Low Resolution Grayscale Images
Get PDFIn this work we present a facial skin detection method, based on a deep learning architecture, that is able to precisely associate a skin label to each pixel of a given image depicting a face. This is an important preliminary step in many applications, such as remote photoplethysmography (rPPG) in which the hearth rate of a subject needs to be estimated analyzing a video of his/her face. The proposed method can detect skin pixels even in low resolution grayscale face images (64 × 32 pixel). A dataset is also described and proposed in order to train the deep learning model. Given the small amount of data available, a transfer learning approach is adopted and validated in order to learn to solve the skin detection problem exploiting a colorization network. Qualitative and quantitative results are reported testing the method on different datasets and in presence of general illumination, facial expressions, object occlusions and it is able to work regardless of the gender, age and ethnicity of the subject
Breast Lesion Detection from Mammograms Using Deep Convolutional Neural Networks
No full textMammography has a central role in screening and diagnosis of breast lesions, allowing early detection of the pathology and reduction of fatal cases. Deep Convolutional Neural Networks have shown a great potentiality to address the issue of early detection of breast cancer with an acceptable level of accuracy and reproducibility. In the present paper, we illustrate the development of a deep learning study aimed to process and classify lesions in mammograms with the use of slender neural networks not yet used in literature. For this reason, a traditional convolution network was compared with a novel one obtained making use of much more efficient depth wise separable convolution layers. Preliminary numerical results are detailed and future plans outlined
A framework for interpreting, modeling and recognizing human body gestures through 3D eigenpostures
No full textAccurate characterization of embedded Structure from Motion
No full textTrajectory estimation and 3d scene reconstruction from single camera, e.g. Structure from Motion, is going to have a central role in the future of automotive industry. Typical appliance fields will be: Collisions avoidance with any kind of object (people included), parking assisted maneuvers and many more. Indeed various countries are becoming more and more concerned about road traffic safety and therefore through its 'Advanced Program', EuroNCAP rewards vehicle manufacturers who employ Advanced Safety Technologies that assists the driver. This paper had mainly two different goals: (1) to describe the implementation of a state of art Structure from Motion pipeline able to run in real time with embedded fish-eye camera, which includes nonlinear optimization (i.e. local bundle adjustment); (2) to demonstrate quantitatively its performances on a synthetic test space specifically designed for its characterization in term of accuracy
Biometric Signals Estimation Using Single Photon Camera and Deep Learning
Get PDFThe problem of performing remote biomedical measurements using just a video stream of a subject face is called remote photoplethysmography (rPPG). The aim of this work is to propose a novel method able to perform rPPG using single-photon avalanche diode (SPAD) cameras. These are extremely accurate cameras able to detect even a single photon and are already used in many other applications. Moreover, a novel method that mixes deep learning and traditional signal analysis is proposed in order to extract and study the pulse signal. Experimental results show that this system achieves accurate results in the estimation of biomedical information such as heart rate, respiration rate, and tachogram. Lastly, thanks to the adoption of the deep learning segmentation method and dependability checks, this method could be adopted in non-ideal working conditions—for example, in the presence of partial facial occlusions
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Early Detection of Partially Emerged Large Scale Marine Debris Based on Laser Pulses
No full textThe Large Scale Marine Debris (LSMD), or drifting objects, pose a serious threat to navigation safety, be they containers, dispersed cargo, large trunks, marine animals, small boats or other large-sized scattered materials. Specifically, in the case of containers, it is estimated that over 10,000 of the approximately 100 million that cross seas and oceans are dispersed each year. Several reported incidents have caused significant dents on ships hulls and in some cases, breaches leading to the sinking of vessels. In many cases, on-board devices such as radar or sonar are able to effectively detect completely emerged or submerged obstacles, respectively, but the presence of partially emerged floating bodies is more difficult to detect due to the significant disturbance introduced by the wave motion. In this article, we present a method based on the photothermal effect which allows for the detection of floating objects even at great distances (500m) through the collimated light of a laser, enabling turning operations for even large vessels and avoiding collision with the obstacle
Deep Learning Coronary Artery Centerlines Mapping from Contrast-Enhanced CT Images of the Heart
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