Results 41 to 50 of about 32,124 (206)

3-Dimensional Object Recognition Using 1-Dimensional Capsule Neural Networks [PDF]

2022 International Conference on Emerging Techniques in Computational Intelligence (ICETCI), 2022
Currently, indoor home object recognition systems lack the degree of accuracy required for reliable automated operations. In this paper, a 3-Dimensional (3D) object recognition deep neural network system, capable of recognizing indoor objects from 3D images with a view to assisting indoor robotic devices in performing home tasks, is presented.
Basu, Amlan, Kaewrak, Keerati, Petropoulakis, Lykourgos, Di Caterina, Gaetano, Soraghan, John   +4 more
openaire   +1 more source

Graph Capsule Convolutional Neural Networks

, 2018
Graph Convolutional Neural Networks (GCNNs) are the most recent exciting advancement in deep learning field and their applications are quickly spreading in multi-cross-domains including bioinformatics, chemoinformatics, social networks, natural language processing and computer vision.
Verma, Saurabh, Zhang, Zhi-Li
openaire   +2 more sources

Learning Capsules for SAR Target Recognition

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
Deep learning has been successfully utilized in synthetic aperture radar (SAR) automatic target recognition tasks and obtained state-of-the-art results. However, current deep learning algorithms do not perform well when SAR images are occluded, noisy, or
Yunrui Guo, Zongxu Pan, Meiming Wang, Ji Wang, Wenjing Yang   +4 more
doaj   +1 more source

CBIR system using Capsule Networks and 3D CNN for Alzheimer's disease diagnosis

Informatics in Medicine Unlocked, 2019
Alzheimer’s disease (AD) is an irreversible disorder of the brain related to loss of memory, commonly seen in the elderly and aging population. Implementation of revolutionary computer aided diagnosis techniques with Content Based Image Retrieval (CBIR ...
K.R. Kruthika, Rajeswari, H.D. Maheshappa   +2 more
doaj   +3 more sources

Multilevel Capsule Weighted Aggregation Network Based on a Decoupled Dynamic Filter for Remote Sensing Scene Classification

IEEE Access, 2021
The improvement of remote sensing scene classification(RSSC) by effectively extracting discriminant representations for complex and diverse scenes remains a challenging task. The capsule network(CapsNet) can encode the spatial relationship of features in
Chunyuan Wang, Yang Wu, Yihan Wang, Yiping Chen, Yan Gao   +4 more
doaj   +1 more source

Multi-labeled Relation Extraction with Attentive Capsule Network

, 2018
To disclose overlapped multiple relations from a sentence still keeps challenging. Most current works in terms of neural models inconveniently assuming that each sentence is explicitly mapped to a relation label, cannot handle multiple relations properly
Jia, Weijia, Li, Pengshuai, Zhang, Xinsong, Zhao, Hai   +3 more
core   +1 more source

A Capsule Decision Neural Network Based on Transfer Learning for EEG Signal Classification

Biomimetics
Transfer learning is the act of using the data or knowledge in a problem to help solve different but related problems. In a brain computer interface (BCI), it is important to deal with individual differences between topics and/or tasks. A kind of capsule
Wei Zhang, Xianlun Tang, Xiaoyuan Dang, Mengzhou Wang   +3 more
doaj   +1 more source

Capsule Networks Showed Excellent Performance in the Classification of hERG Blockers/Nonblockers

Frontiers in Pharmacology, 2020
Capsule networks (CapsNets), a new class of deep neural network architectures proposed recently by Hinton et al., have shown a great performance in many fields, particularly in image recognition and natural language processing. However, CapsNets have not
Yiwei Wang, Yiwei Wang, Lei Huang, Lei Huang, Siwen Jiang, Yifei Wang, Jun Zou, Hongguang Fu, Shengyong Yang   +8 more
doaj   +1 more source

A Combination of Dilated Self-Attention Capsule Networks and Bidirectional Long- and Short-Term Memory Networks for Vibration Signal Denoising

Machines, 2022
As scalar neurons of traditional neural networks promote dimension reduction caused by pooling, it is a difficult task to extract the high-dimensional spatial features and long-term correlation of pure signals from the noisy vibration signal.
Youming Wang, Gongqing Cao, Jiali Han
doaj   +1 more source

Unsupervised Odometry and Depth Learning for Endoscopic Capsule Robots

, 2018
In the last decade, many medical companies and research groups have tried to convert passive capsule endoscopes as an emerging and minimally invasive diagnostic technology into actively steerable endoscopic capsule robots which will provide more ...
Almalioglu, Yasin, Giracoglu, Can, Ibrahimli, Nail, Ornek, Evin Pinar, Sitti, Metin, Turan, Mehmet, Yanik, Mehmet Fatih   +6 more
core   +1 more source