Deep learning techniques have boosted the performance of hyperspectral image (HSI)
classification. In particular, convolutional neural networks (CNNs) have shown superior …

… are very important for medical image analysis. In this paper, an enhanced capsule network
is proposed for medical image classification. For the proposed capsule network, the feature …

… In this work, we develop an easy-to-implement capsule network to alleviate the … methods
for the capsule network and build a novel architecture for HSIs classification. Compared to …

… image classification. To solve this problem, in this paper we present a two-stage endoscopic
image classification … of midlevel CNN features and a capsule network. Specifically, the core …

… capsule network (CapsNet) preserves the hierarchy between different parts of the entity in an
image … , the hybrid capsule network (HCapsNet), for HSI classification. HCapsNet employs 2…

… , in this study, we considered a deeper capsule network based on CapsNet with more layers
to solve the problem of limited labeled samples in the HSI classification. In this section, we …

… two novel classification frameworks for hyperspectral image (HSI) based on capsule network
(CapsNet), which could address the drawbacks of convolutional neural network (CNN) and …

… This work focuses on reviewing capsule network literature applied to image classification …
capsule network-based architectures’ intuition, formulation, and working for image classification…

… between different types of breast cancer histological images – normal tissue or carcinoma
(… , based on convolutional capsule network, for classification of four types of images of breast …

… capsule networks in order to achieve a highly accurate classification of HSIs while significantly
reducing the network … Specifically, based on Hinton’s capsule networks, we develop a …