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Combining Fully Convolutional and Recurrent Neural Networks for 3D Biomedical Image Segmentation

by Jianxu Chen , Lin Yang , Yizhe Zhang , Mark Alber , Danny Z Chen
"... Abstract Segmentation of 3D images is a fundamental problem in biomedical image analysis. Deep learning (DL) approaches have achieved state-of-the-art segmentation performance. To exploit the 3D contexts using neural networks, known DL segmentation methods, including 3D convolution, 2D convolution ..."
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Abstract Segmentation of 3D images is a fundamental problem in biomedical image analysis. Deep learning (DL) approaches have achieved state-of-the-art segmentation performance. To exploit the 3D contexts using neural networks, known DL segmentation methods, including 3D convolution, 2D convolution

Fully convolutional neural networks for crowd segmentation. arXiv preprint arXiv:1411.4464

by Kai Kang, Xiaogang Wang , 2014
"... In this paper, we propose a fast fully convolutional neu-ral network (FCNN) for crowd segmentation. By replacing the fully connected layers in CNN with 1 × 1 convolution kernels, FCNN takes whole images as inputs and directly outputs segmentation maps by one pass of forward prop-agation. It has the ..."
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In this paper, we propose a fast fully convolutional neu-ral network (FCNN) for crowd segmentation. By replacing the fully connected layers in CNN with 1 × 1 convolution kernels, FCNN takes whole images as inputs and directly outputs segmentation maps by one pass of forward prop-agation. It has

Automatic detection of invasive ductal carcinoma in whole slide images with Convolutional Neural Networks

by Angel Cruz-roaa, Ajay Basavanhallyb, Hannah Gilmorec, Michael Feldm, Shridar Ganesane, Natalie Shihd, John Tomaszewskif, Anant Madabhushig
"... This paper presents a deep learning approach for automatic detection and visual analysis of invasive ductal carcinoma (IDC) tissue regions in whole slide images (WSI) of breast cancer (BCa). Deep learning approaches are learn-from-data methods involving computational modeling of the learning process ..."
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features and classifier. The DL framework in this paper extends a number of convolutional neural networks (CNN) for visual semantic analysis of tumor regions for diagnosis support. The CNN is trained over a large amount of image patches (tissue regions) from WSI to learn a hierarchical part

UNSUPERVISED DEEP FEATURE EXTRACTION OF HYPERSPECTRAL IMAGES

by Adriana Romero, Carlo Gatta, Gustavo Camps-valls
"... This paper presents an effective unsupervised sparse feature learn-ing algorithm to train deep convolutional networks on hyperspectral images. Deep convolutional hierarchical representations are learned and then used for pixel classification. Features in lower layers present less abstract representa ..."
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This paper presents an effective unsupervised sparse feature learn-ing algorithm to train deep convolutional networks on hyperspectral images. Deep convolutional hierarchical representations are learned and then used for pixel classification. Features in lower layers present less abstract

Active Mask Framework for Segmentation of Fluorescence Microscope Images

by Gowri Srinivasa, Advisor Prof, Prof Matthew, C. Fickus, Prof Adam, D. Linstedt, Prof Robert, F. Murphy
"... m]]l]]s¶D]]¿÷mB]iv]b]oD]m¶¨]iv]§]iv]r]j]t¿rv]]irj]]t]]m] / | ap]]r¿]ÎNy]s¶D]]mb¶r]ix} Û]Ix]]rd]mb]} p—N]t]o%ism] in]ty]m] / || Û]Is]¡uÎc]rN]]riv]nd]p]*N]m]st¶ I always bow to Śri ̄ Śāradāmbā, the limitless ocean of the nectar of compassion, who bears a rosary, a vessel of nectar, the symbol of ..."
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of knowledge and a book in Her lotus hands. Dedicated to the Lotus Feet of the revered Sadguru. This thesis presents a new active mask (AM) framework and an algorithm for segmenta-tion of digital images, particularly those of punctate patterns from fluorescence microscopy. Fluorescence microscopy has greatly

Polyp detection in Colonoscopy Videos Using Deeply-Learned Hierarchical Features

by Sungheon Park, Myunggi Lee, Nojun Kwak
"... This paper summarizes the method of polyp detection in colonoscopy images and provides preliminary results to participate in ISBI 2015 Grand Challenge on Automatic Polyp Detection in Colonoscopy videos. The key aspect of the proposed method is to learn hierarchical features using convolutional neura ..."
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neural network. The features are learned in different scales to provide scale-invariant features through the convolutional neural network, and then each pixel in the colonoscopy image is classified as polyp pixel or non-polyp pixel through fully connected network. The result is refined via smooth

SIMULATION, DEVELOPMENT AND DEPLOYMENT OF MOBILE WIRELESS SENSOR NETWORKS FOR MIGRATORY BIRD TRACKING

by Bird Tracking, William P. Bennett, William P., Development, Deployment Of, Mobile Wireless Sensor, William P. Bennett, William P. Bennett, Adviser Mehmet, C. Vuran , 2012
"... This thesis presents CraneTracker, a multi-modal sensing and communication system for monitoring migratory species at the continental level. By exploiting the robust and extensive cellular infrastructure across the continent, traditional mobile wireless sensor networks can be extended to enable reli ..."
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This thesis presents CraneTracker, a multi-modal sensing and communication system for monitoring migratory species at the continental level. By exploiting the robust and extensive cellular infrastructure across the continent, traditional mobile wireless sensor networks can be extended to enable

Perspective An Online Bioinformatics Curriculum

by David B. Searls
"... Abstract: Online learning initia-tives over the past decade have become increasingly comprehen-sive in their selection of courses and sophisticated in their presen-tation, culminating in the recent announcement of a number of consortium and startup activities that promise to make a university educat ..."
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course catalog, together with editorial commentary, and an assessment of strengths, weaknesses, and likely future directions for open online learning in this field. Online Learning Comes of Age Online academic ‘‘courseware’ ’ at the university level has now been available to the public for a decade

4. TITLE AND SUBTITLE A Practical Theory of Micro-Solar Power Sensor Networks

by Jaein Jeong , 2009
"... Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments ..."
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Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information,

Thesis Advisor Accepted by.......Gakenhimer..

by Gregory A. Rossel, Fiichael J. Shiffer, Ralph Gakenheimer, Gregory A. Rossel
"... ussRaNIte ..."
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