APRON
发表于 2025-3-23 13:02:07
Eleonora Solari,Andrea Moriondo the classification of celiac disease. We will show that the deeper CNN architectures outperform these comparison approaches and that combining CNNs with linear support vector machines furtherly improves the classification rates for about 3–7% leading to distinctly better results (up to 97%) than those of the comparison methods.
浅滩
发表于 2025-3-23 15:51:42
Convolutional Neural Network Architectures for the Automated Diagnosis of Celiac Disease, the classification of celiac disease. We will show that the deeper CNN architectures outperform these comparison approaches and that combining CNNs with linear support vector machines furtherly improves the classification rates for about 3–7% leading to distinctly better results (up to 97%) than those of the comparison methods.
resilience
发表于 2025-3-23 19:12:39
Conference proceedings 201713 initial submissions. The papers are organized on topical secttion such as computer vision, graphics, robotics, medical imaging, external tracking systems, medical device controls systems, information processing techniques, endoscopy planning and simulation..
收藏品
发表于 2025-3-23 22:11:52
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Lacunar-Stroke
发表于 2025-3-24 04:23:04
0302-9743 hop on Computer Assisted and Robotic Endoscopy, CARE 2016, held in conjunction with MICCAI 2016, in Athens, Greece, in October 2016.. .The 11 revised full papers were carefully selected out of 13 initial submissions. The papers are organized on topical secttion such as computer vision, graphics, rob
palliate
发表于 2025-3-24 09:57:07
Toussaint Houeninvo,Philippe Sèdédjiscopy image classification. Experiments on a three class (abnormal, normal, uninformative) white-light colonoscopy image dataset with 2800 images show that the proposed feature perform better than popular hand-designed features used in the medical as well as in the computer vision literature for image classification.
palliate
发表于 2025-3-24 13:40:24
Extended Multi-resolution Local Patterns - A Discriminative Feature Learning Approach for Colonoscoscopy image classification. Experiments on a three class (abnormal, normal, uninformative) white-light colonoscopy image dataset with 2800 images show that the proposed feature perform better than popular hand-designed features used in the medical as well as in the computer vision literature for image classification.
COW
发表于 2025-3-24 17:41:14
Conference proceedings 2017opy, CARE 2016, held in conjunction with MICCAI 2016, in Athens, Greece, in October 2016.. .The 11 revised full papers were carefully selected out of 13 initial submissions. The papers are organized on topical secttion such as computer vision, graphics, robotics, medical imaging, external tracking s
祖传
发表于 2025-3-24 21:06:19
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creditor
发表于 2025-3-24 23:28:30
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