… Our Contributions In this paper, we present a multi-scale and rotation-invariant convolutional
neural network (MRCNN) which is capable of classifying the lung texture pattern more …

… texture Convolutional Neural Networks (CNN) to improve the classification performance of
pulmonary … filter banks in convolutional neural networks for texture classification,” Pattern …

… and evaluate a convolutional neural network (CNN), designed for the classification of ILD …
and principles on the design of CNN architectures for similar texture classification problems. …

… Local Binary Pattern is Powerful feature for texture classification. Its computational simplicity
property is very important, which helps to analyse images in real-time settings. It divides the …

… convolutional neural network (CNN) architectures are presented in this paper, based on the
original networks … , such as texture classification, a well-designed deep learning architecture …

… In this paper, an advanced technique for lung-nodule detection by using a hybrid feature
set and artificial neural network is proposed. Initially, the lung volume is segmented from the …

… In this paper, we compare three machine learning approaches for lung sounds classification…
the third approach is based on the design of convolutional neural networks (CNN). In the first …

… This paper presented a new CAD system for lung texture classification issued from
combination between a 3D parametric approach and a convolutional neural network-based …

… problem of lung nodule diagnostic classification based on … and textural feature descriptors
for the classification task, we … heterogeneity by utilizing Convolutional Neural Networks (CNN) …

… a new deep convolutional neural network (CNN) architecture to achieve the classification task
… A publicly available texture classification benchmark Kylberg Texture Dataset (KTD) [18] is …