کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4969389 1449930 2017 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Design, analysis and application of a volumetric convolutional neural network
ترجمه فارسی عنوان
طراحی، تجزیه و تحلیل و کاربرد یک شبکه عصبی کانولاسیون حجمی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
The design, analysis and application of a volumetric convolutional neural network (VCNN) are studied in this work. Although many CNNs have been proposed in the literature, their design is empirical. In the design of the VCNN, we propose a feed-forward K-means clustering algorithm to determine the filter number and size at each convolutional layer systematically. For the analysis of the VCNN, the cause of confusing classes in the output of the VCNN is explained by analyzing the relationship between the filter weights (also known as anchor vectors) from the last fully-connected layer to the output. Furthermore, a hierarchical clustering method followed by a random forest classification method is proposed to boost the classification performance among confusing classes. For the application of the VCNN, we examine the 3D shape classification problem and conduct experiments on a popular ModelNet40 dataset. The proposed VCNN offers the state-of-the-art performance among all volume-based CNN methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Visual Communication and Image Representation - Volume 46, July 2017, Pages 128-138
نویسندگان
, , ,