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Inappropriate medication use such as wrong drug or wrong dose intake can be harmful to patients. In this work we present a method to automatically identify a pill from a single image using Convolutional Neural Network (CNN). We first localize the pill in the image by detecting the region with the highest concentration of edges. To overcome the challenge of minimal labeled training data and domain...
In this paper we study the measurability and variability of manually annotated characteristic descriptors on a forensic relevant face dataset. Characteristic descriptors are facial features (landmarks, shapes, etc.) that can be used during forensic case work. With respect to measurability, we observe that a significant proportion cannot be determined in images representative of forensic case work...
The detection of cells and nuclei is a crucial step for the automatic analysis of digital pathology slides and as such for the quantification of the phenotypic information contained in tissue sections. This task is however challenging because of high variability in size, shape and textural appearance of the objects to be detected and of the high variability of tissue appearance. In this work, we propose...
Human's everyday environment is an open environment in which objects with new shapes, colors or textures frequently appear. Enabling robots to deal with such environments and to manipulate those objects raises a difficult challenge: how to recognize an object? How to distinguish it from the background? An approach is proposed here to allow the robot to find this segmentation on its own. It relies...
Despite the progress that has been made in the field of program visualization, programmers nowadays still rely on inserting extra code (e.g. print statements) to visualize complicated program states during debugging. There are many obstacles that have impeded and continue to impede program visualization for practical use. One such major obstacle is that a wide variety of data types and interpretations...
Recently, the use of object proposals has been much introduced in the field of salient object segmentation methods. Object proposal methods provide a limited set of proposals per image which can successively be analyzed on their saliency. In this context, we regard saliency map computation as a regression problem and we used object proposals (selective search) to compute the saliency map. Our method...
In this paper, a novel automatic approach to extract the inner lips contour of speakers without using artifices is proposed. This method is based on a recent facial contour extraction model developed in computer vision, called Constrained Local Neural Field (CLNF), which provides 8 characteristic points (landmarks) defining the inner lips contour. However, directly applied to our visual data including...
Recovering depth information from a single still image is an important problem in computer vision. However, the problem is difficult and challenging because it has an infinite number of solutions. To address this issue, humans use numerous visual cues to infer depth. Much progress has been made towards an understanding of the visual mechanisms involved in 3D perception. Such an understanding provides...
We have developed an efficient information-maximization method for computing the optimal shapes of tuning curves of sensory neurons by optimizing the parameters of the underlying feedforward network model. When applied to the problem of population coding of visual motion with multiple directions, our method yields several types of tuning curves with both symmetric and asymmetric shapes that resemble...
Representative distribution of body shapes is needed when simulating crowds in real-world situations, e.g., for city or event planning. Visual realism and plausibility are often also required for visualization purposes, while these are the top criteria for crowds in entertainment applications such as games and movie production. Therefore, achieving representative and visually plausible body-shape...
Vision is vital to decision making, as humans naturally trust their eyes to enhance situation awareness. Yet the modern age has overwhelmed humans with massive amounts of visual information, which is problematic in time sensitive and mission critical situations, such as emergency management and disaster response. More efficient search and retrieval systems address some of these issues, which is why...
Most objects are designed for certain functionalities. For example, a knife is designed for cutting, and a hammer for pounding. Indeed, functionalities are not related to the objects themselves but to certain object parts, e.g., the blade of a knife affords cutting. A part can have different shapes and can exist in different objects such as a scraper or a peeler, but it carries the same functional...
Learning visual attributes is an effective approach for zero-shot recognition. However, existing methods are restricted to learning explicitly nameable attributes and cannot tell which attributes are more important to the recognition task. In this paper, we propose a unified framework named Grouped Simile Ensemble (GSE). We claim our contributions as follows. 1) We propose to substitute explicit attribute...
Image retrieval and classification in medical domain are the two important aspects in decision making and automatic annotation of benign and malignant images. These processes improve the decision making during decease identification. Image classification is usually done by checking image visual or semantic content similarity. Image content may be represented by its low level visual features referring...
Geometry is an interesting area of mathematics. It opens to many different approaches and closely relates to our everyday lives. However, when students recall their experiences of learning geometry, many of them regards it as not only unpleasant experiences but often also difficult experiences. The traditional materials and tools such as pens, papers, blackboards, textbooks and/or classical methodologies...
The main focus of this work is on analysis of the Differential Doppler method having a designed algorithm for computing and 2-D visualization of the iso doppler curves for three-positional and two-positional moving stations with a stationary target. This work also describes the effect of the target position and velocity vectors of the moving stations on the shape of the iso doppler curves. Using the...
An image retrieval system is a software system which is used to browse, search and retrieve images from a large database of digital images. It is a specialized search to find digital images. In most applications of image processing, it becomes necessary to find images by using text, keywords or by using any other features of an image. The conventional or traditional methods of image retrieval includes...
Content-based image retrieval (CBIR) is a technique uses visual contents such as color, texture and shape to search images from large scale image databases according to users' interest. In a CBIR, visual image content is represented in form of image features, which are extracted automatically and there is no manual intervention, thus eliminating the dependency on humans in the feature extraction stage...
The Radial Basis Function (RBF) interpolation is a common technique for scattered data interpolation. We present and test an approach of RBF interpolation on a sphere which uses the spherical distance on the surface of the sphere instead of the Euclidian distance. We show how the interpolation of vector field data depends on the value of shape parameter of RBF and find the optimal shape parameter...
The effective application of spatio-temporal network models to neuroimaging data is an emerging challenge in the field of neuroscience, and could help scientists to better understand the behavior of the brain across a range of different experiments. One of the main problems with deriving spatiotemporal networks is that it is difficulty to provide a clear view of computed results. In this paper, we...
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