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ROBIDOUX LUMBER

ST PIERRE JOLYS-Canada

Company Name:
Corporate Name:
ROBIDOUX LUMBER
Company Title:  
Company Description:  
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Company Address: 477 Turenne St,ST PIERRE JOLYS,MB,Canada 
ZIP Code:
Postal Code:
R0A1V0 
Telephone Number: 2044337458 
Fax Number: 2044337025 
Website:
 
Email:
 
USA SIC Code(Standard Industrial Classification Code):
521142 
USA SIC Description:
Lumber-Retail 
Number of Employees:
1 to 4 
Sales Amount:
$1 to 2.5 million 
Credit History:
Credit Report:
Excellent 
Contact Person:
Joseph Robidoux 
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Company News:
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  • Data Science Bowl 2017 肺癌预测数据 | 数据集 | HyperAI超神经
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  • Deep Convolutional Neural Networks for Lung Cancer Detection
    Here we demonstrate a CAD system for lung cancer clas-sification of CT scans with unmarked nodules, a dataset from the Kaggle Data Science Bowl 2017 Thresholding was used as an initial segmentation approach to to segment out lung tissue from the rest of the CT scan
  • 2nd place solution for the 2017 national datascience bowl
    For this dataset doctors had meticulously labeled more than 1000 lung nodules in more than 800 patient scans The LUNA16 competition also provided non-nodule annotations
  • GitHub - owkin DSB2017: Data Science Bowl 2017 : Lung Cancer Detection
    We developed two methods, both based on nodule detection using the LUNA dataset Both methods pre-process the images to get a fixed 1mm x 1mm x 1mm resolution and segment the lungs using thresholding, morphological operations and connected components selection
  • Lung Cancer Detection and Classification with 3D Convolutional Neural . . .
    This paper demonstrates a computer-aided diagnosis (CAD) system for lung cancer classification of CT scans with unmarked nodules, a dataset from the Kaggle Data Science Bowl, 2017
  • Deep Learning for Lung Cancer Detection: Tackling the Kaggle Data . . .
    Our multi-stage framework detects nodules in 3D lung CAT scans, determines if each nodule is malignant, and nally assigns a cancer probability based on these results We discuss the challenges and advantages of our framework In the Kaggle Data Science Bowl 2017, our framework ranked 41st out of 1972 teams positive rate in diagnosis
  • DSB17 3d lung nodule classifier - GitHub
    This repository contains the first stage of my solution for the 2017 Kaggle data science bowl (ranked in the top 3%) It consists in a 3d convnet for the classification of lung proposed tissue regions for nodules tumor in lung CT scans
  • Kaggle Data Science Bowl 2017: Detecting Lung Cancer
    The objective was to detect lung cancer based on CT scans of the chest from individuals diagnosed with cancer within a year Despite their lack of specific knowledge in medical image analysis or cancer prediction, the team secured 9th place in the competition
  • GitHub - anlthms dsb-2017: Data Science Bowl 2017
    This code is for training a 3D Convolutional Neural Network on the LUNA16 dataset in order to detect malignant nodules I am hopeful that this can be used as the first step towards solving the DSB 2017 challenge




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