Results 31 to 40 of about 18,989 (190)
Shelf Commodity Identification Method Based on Hybrid Fully Convolutional Automatic Encoder
IEEE Access, 2019 At present, the semantic information segmentation algorithms mainly include FCN (Fully Convolutional Network), PSPNet (Pyramid Scene Parsing Network), Deeplab and so on. In view of the inadequate results of features extracted by these algorithms from RGB
Aofeng Cheng, Guodong Chen, Zheng Wang
doaj +1 more source
Mathematical Biosciences and Engineering, 2019 Recently, fully convolutional network (FCN) has been successfully used to locate spliced regions in synthesized images. However, all the existing FCN-based algorithms use real-valued FCN to process each channel separately.
Beijing Chen +5 more
doaj +1 more source
An automatic skin lesion segmentation system with hybrid FCN-ResAlexNet
Engineering Science and Technology, an International Journal, 2022 Skin cancer is a serious global health concern with high morbidity and mortality rates. Therefore, computer-aided automatic diagnostic systems are essential to diagnose skin lesions successfully.
Sezin Barın, Gür Emre Güraksın
doaj +1 more source
Joint Object and Part Segmentation using Deep Learned Potentials [PDF]
, 2015 Segmenting semantic objects from images and parsing them into their respective semantic parts are fundamental steps towards detailed object understanding in computer vision. In this paper, we propose a joint solution that tackles semantic object and part
Cohen, Scott +5 more
core +1 more source
A Novel Deep Fully Convolutional Network for PolSAR Image Classification
Remote Sensing, 2018 Polarimetric synthetic aperture radar (PolSAR) image classification has become more and more popular in recent years. As we all know, PolSAR image classification is actually a dense prediction problem.
Yangyang Li +3 more
doaj +1 more source
Improved Fully Convolutional Network with Conditional Random Fields for Building Extraction
Remote Sensing, 2018 Building extraction from remotely sensed imagery plays an important role in urban planning, disaster management, navigation, updating geographic databases, and several other geospatial applications.
Sanjeevan Shrestha, Leonardo Vanneschi
doaj +1 more source
Dual-Branch Fully Convolutional Network (DB-FCN): An End-to-End Model for Nucleus Detection
Christopher George
openalex +2 more sources
Remote Sensing, 2022 Polarimetric synthetic aperture radar (PolSAR) image classification is a pixel-wise issue, which has become increasingly prevalent in recent years. As a variant of the Convolutional Neural Network (CNN), the Fully Convolutional Network (FCN), which is ...
Wen Xie, Licheng Jiao, Wenqiang Hua
doaj +1 more source
Leida xuebao, 2019 For the fast detection of ships in large-scale remote sensing images, a cascade convolutional neural network is proposed, which is a cascade combination of two Fully Convolutional Neural networks (FCNs), the target FCN for Prescreening (P-FCN), and the ...
CHEN Huiyuan +4 more
doaj +1 more source
Automatic 3D bi-ventricular segmentation of cardiac images by a shape-refined multi-task deep learning approach [PDF]
, 2019 Deep learning approaches have achieved state-of-the-art performance in cardiac magnetic resonance (CMR) image segmentation. However, most approaches have focused on learning image intensity features for segmentation, whereas the incorporation of ...
Bai, Wenjia +9 more
core +3 more sources