3,338 research outputs found
Multi-Level Batch Normalization In Deep Networks For Invasive Ductal Carcinoma Cell Discrimination In Histopathology Images
Breast cancer is the most diagnosed cancer and the most predominant cause of
death in women worldwide. Imaging techniques such as the breast cancer
pathology helps in the diagnosis and monitoring of the disease. However
identification of malignant cells can be challenging given the high
heterogeneity in tissue absorbotion from staining agents. In this work, we
present a novel approach for Invasive Ductal Carcinoma (IDC) cells
discrimination in histopathology slides. We propose a model derived from the
Inception architecture, proposing a multi-level batch normalization module
between each convolutional steps. This module was used as a base block for the
feature extraction in a CNN architecture. We used the open IDC dataset in which
we obtained a balanced accuracy of 0.89 and an F1 score of 0.90, thus
surpassing recent state of the art classification algorithms tested on this
public dataset.Comment: 4 pages, 5 figure
Liver lesion segmentation informed by joint liver segmentation
We propose a model for the joint segmentation of the liver and liver lesions
in computed tomography (CT) volumes. We build the model from two fully
convolutional networks, connected in tandem and trained together end-to-end. We
evaluate our approach on the 2017 MICCAI Liver Tumour Segmentation Challenge,
attaining competitive liver and liver lesion detection and segmentation scores
across a wide range of metrics. Unlike other top performing methods, our model
output post-processing is trivial, we do not use data external to the
challenge, and we propose a simple single-stage model that is trained
end-to-end. However, our method nearly matches the top lesion segmentation
performance and achieves the second highest precision for lesion detection
while maintaining high recall.Comment: Late upload of conference version (ISBI
Deductive Optimization of Relational Data Storage
Optimizing the physical data storage and retrieval of data are two key
database management problems. In this paper, we propose a language that can
express a wide range of physical database layouts, going well beyond the row-
and column-based methods that are widely used in database management systems.
We use deductive synthesis to turn a high-level relational representation of a
database query into a highly optimized low-level implementation which operates
on a specialized layout of the dataset. We build a compiler for this language
and conduct experiments using a popular database benchmark, which shows that
the performance of these specialized queries is competitive with a
state-of-the-art in memory compiled database system
Do Not Forget the "How" along with the "What": Improving the Transparency of Sustainability Reports
Considerable resources are invested in producing sustainability reports, yet few organizations reap the transparency benefits they promise. This article explores the way ten leading global fashion companies use a combination of data visualization and placement, stakeholder-driven interactive content, and multi-media and immersive content to build the trust necessary to improve their reporting and transparency. While few organizations have the resources of the global fashion giants, this article proposes a four-stage framework that guides managers through a step-change of systematic and targeted improvement
THE PERFORMANCE OF BDS RELATIVE POSITIONING USAGE WITH REAL OBSERVATION DATA
With the first phase of COMPASS/BeiDou-2 (BDS) completed, the assessment ofpositioning performance and the characterization of its system are analyzed andpresented. Pseudo-range and carrier phase measurements modulated on B1 and B2have been collected in Shanghai, from 00:00 to 24:00 on 28 December, 2012.Compared with GPS, visibility and measurement quality of BDS’s GEO, IGSO andMEO satellites are analyzed. DOP during the whole orbital period is also analyzedthe results demonstrate that BDS’s HDOP is better than GPS’s one, but VDOPopposite. Furthermore, the result of positioning is also presented and analyzed.Short baselines are estimated by standalone BDS and GPS’s carrier phasemeasurement, respectively, using 48 segmentations of observations during a wholeday (24 hours, each segmentation, is about 30 minutes observation). The analysis ofstatic relative positioning demonstrates that BDS could achieve to millimeter level,corresponding to GPS. Kinematic result is produced by double differenced carrierphase observations with the ambiguities fixed under the constraint of precise shortbaseline.The result shows that the centimeter accuracy could be achieved. Whencomparing the results of kinematic baseline solutions, performance of BDS is worsethan GPS on North and Up components, but oppositely on the component of East inthe kinematic baseline processing
Development of a prototype smart home intelligent lighting control architecture using sensors onboard a mobile computing system
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