In this work, we present a novel approach for training Generative Adversarial Networks (GANs). Using the attention maps produced by a TeacherNetwork we are able to improve the quality of the generated images as well as perform weakly object localization on the generated images. To this end, we generate images of HEp-2 cells captured with Indirect Imunofluoresence (IIF) and study the ability of ...

X­ray mammography is regarded as the most effective tool for the detection and diagnosis of breast cancer, but the interpretation of mammograms is a difficult and error­prone task. Computer­aided detection (CADe) systems address the problem that radiologists often miss signs of cancers that are retrospectively visible in mammograms. Furthermore, computer­aided diagnosis ...

In this paper, we learn to discover composite operators and features that are evolved from combinations of primitive image processing operations to extract regions-of-interest (ROIs) in images. Our approach is based on genetic programming (GP). The motivation for using GP is that there are a great many ways of combining these primitive operations and the human expert, limited by experience, kno...

Detection of some interest points on an object is useful for many applications, such as local shape description of the object, recognition of the object in clutter environment etc. The same object present in different images can have some geometric and photometric transformations with respect to one another. The detection method should be robust to all these transformations. We describe relativ...

Graphs emerge naturally in many domains, such as social science, neuroscience, transportation engineering, and more. In many cases, such graphs have millions or billions of nodes and edges, and their sizes increase daily at a fast pace. How can researchers from various domains explore large graphs interactively and efficiently to find out what is ‘important’? How can multiple researchers explor...

The Argo array provides a unique dataset to explore variability of the subsurface ocean interior. This study considers the subtropical North Pacific Ocean during the period from 2004 to 2011, when Argo coverage has been relatively complete in time and space. Two distinct patterns of Argo dynamic height transport function (d DH) are observed: in 2004/05, the gyre is stronger, and in 2008/09 it i...

4 1 Neurobiology of the Cerebral Cortex and its Thickness 5 1.1 The Structure and Function of the Cerebral Cortex . . . . . . . . . . . . . . . . . . . 5 1.2 The Development of The Cerebral Cortex . . . . . . . . . . . . . . . . . . . . . . . . 6 1.2.1 Prenatal Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.2.2 Infancy and Early Childhood . . . . . . . . . . . . ....

Infrared Non-Destructive Testing (INDT) is known as an effective and rapid method for nondestructive inspection. It can detect a broad range of near-surface structuring flaws in metallic and composite components. Those flaws are modeled as a smooth contour centered at peaks of stored thermal energy, termed Regions of Interest (ROI). Dedicated methodologies must detect the presence of those ROIs...

A method is described for fusing the results of different feature detection algorithms in order to segment regions in C T (computed tomography) images. While many feature detectors are available, each has its own characteristics strengths and weaknesses. In this work we aim to anticipate the complementary nature of such detectors, and so exploit strengths and tolerate weaknesses in each. To ach...

In this paper, we propose a deep part-based model (DeePM) for symbiotic object detection and semantic part localization. For this purpose, we annotate semantic parts for all 20 object categories on the PASCAL VOC 2012 dataset, which provides information on object pose, occlusion, viewpoint and functionality. DeePM is a latent graphical model based on the state-of-the-art R-CNN framework, which ...