Results 81 to 90 of about 20,298 (224)
Integrating Image Segmentation and Deep Learning to Improve Radio Frequency Propagation Models
International Journal of Satellite Communications and Networking, EarlyView.ABSTRACT This paper proposes a multi‐sensor approach to improve radio frequency (RF) propagation models, which play a key role in the rapidly expanding field of connected vehicle technology. Focusing on the 1‐ to 20‐GHz frequency range, which is critical for both satellite‐to‐vehicle and base station‐to‐vehicle communications, our study introduces a ...
Jonathan Israel +2 more
wiley +1 more source
Remote Sensing, 2018 Fully Convolutional Networks (FCN) has shown better performance than other classifiers like Random Forest (RF), Support Vector Machine (SVM) and patch-based Deep Convolutional Neural Network (DCNN), for object-based classification using orthoimage only ...
Tao Liu, Amr Abd-Elrahman
doaj +1 more source
Remote Sensing, 2019 This paper studies the use of the Fully Convolutional Networks (FCN) model in the extraction of water bodies from Very High spatial Resolution (VHR) optical images in the case of limited training samples.
Liwei Li +5 more
doaj +1 more source
CAAI Transactions on Intelligence Technology, EarlyView.Abstract Brain tumour segmentation employing MRI images is important for disease diagnosis, monitoring, and treatment planning. Till now, many encoder‐decoder architectures have been developed for this purpose, with U‐Net being the most extensively utilised. However, these architectures require a lot of parameters to train and have a semantic gap. Some
Muhammad Zeeshan Aslam +3 more
wiley +1 more source
A Face Spoofing Detection Method Based on Domain Adaptation and Lossless Size Adaptation
IEEE Access, 2020 In this paper, a face spoofing detection method called the Fully Convolutional Network with Domain Adaptation and Lossless Size Adaptation (FCN-DA-LSA) is proposed.
Wenyun Sun +3 more
doaj +1 more source
FCN Approach for Dynamically Locating Multiple Speakers
CoRR, 2020 In this paper, we present a deep neural network-based online multi-speaker localisation algorithm. Following the W-disjoint orthogonality principle in the spectral domain, each time-frequency (TF) bin is dominated by a single speaker, and hence by a single direction of arrival (DOA).
Hodaya Hammer +3 more
openaire +3 more sources
CAAI Transactions on Intelligence Technology, EarlyView.Abstract Abnormalities in the heart's rhythm, known as arrhythmias, pose a significant threat to global health, often leading to severe cardiac conditions and sudden cardiac deaths. Therefore, early and accurate detection of arrhythmias is crucial for timely intervention and potentially life‐saving treatment.
Hasnain Ali Shah +4 more
wiley +1 more source
Dilated FCN: Listening Longer to Hear Better [PDF]
2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), 2019 Deep neural network solutions have emerged as a new and powerful paradigm for speech enhancement (SE). The capabilities to capture long context and extract multi-scale patterns are crucial to design effective SE networks. Such capabilities, however, are often in conflict with the goal of maintaining compact networks to ensure good system generalization.
Shuyu Gong +6 more
openaire +3 more sources
Remote Sensing, 2019 Land cover Classified maps obtained from deep learning methods such as Convolutional neural networks (CNNs) and fully convolutional networks (FCNs) usually have high classification accuracy but with the detailed structures of objects lost or smoothed. In
Nicholus Mboga +5 more
doaj +1 more source
End-Face Localization and Segmentation of Steel Bar Based on Convolution Neural Network
IEEE Access, 2020 Both number manually-counting method and traditional Machine-Vision (MV) number counting strategy are laborious and very time-consuming (sometimes several hours). Thus a new deep learning (DL) fusion model is proposed, which includes object detection and
Yongjian Zhu +3 more
doaj +1 more source