Results 21 to 30 of about 6,343,053 (206)

A Semantic Segmentation Method for Buffer Layer Defect Detection in High Voltage Cable [PDF]

E3S Web of Conferences, 2021
A semantic segmentation method based on the fully convolutional network is proposed to detect the buffer layer defect in high voltage cable automatically. One hundred seventy-seven high-resolution X-ray images of cables are collected.
Jun Zhang, Xiaoli Duan, Yi Xie, Jianjia Duan, Fuyong Huang, Zeyu Zeng   +5 more
doaj   +1 more source

A Comparative Study of Five Networks for Reservoir Classification Based on Geophysical Logging Signals

IEEE Access, 2020
Unconventional reservoir classification suffers low accuracy because of the complex geophysical properties. With good performance and moderate cost, geophysical logging is considered to be of great potential as the compromise solution between seismic and
Kai Zhu, Yonghui Du, Qian Wang, Naihua Ji, Li Zhang   +4 more
doaj   +1 more source

Multi-Scale Fully Convolutional Network-Based Semantic Segmentation for Mobile Robot Navigation

Electronics, 2023
In computer vision and mobile robotics, autonomous navigation is crucial. It enables the robot to navigate its environment, which consists primarily of obstacles and moving objects.
T. Dang, N. Bui
semanticscholar   +1 more source

Application of Deep Convolution Network to Automated Image Segmentation of Chest CT for Patients With Tumor

Frontiers in Oncology, 2021
ObjectivesTo automate image delineation of tissues and organs in oncological radiotherapy by combining the deep learning methods of fully convolutional network (FCN) and atrous convolution (AC).MethodsA total of 120 sets of chest CT images of patients ...
Hui Xie, Hui Xie, Jian-Fang Zhang, Qing Li, Qing Li   +4 more
doaj   +1 more source

Domain‐adapted driving scene understanding with uncertainty‐aware and diversified generative adversarial networks

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract Autonomous vehicles are required to operate in an uncertain environment. Recent advances in computational intelligence techniques make it possible to understand driving scenes in various environments by using a semantic segmentation neural network, which assigns a class label to each pixel.
Yining Hua, Jie Sui, Hui Fang, Chuan Hu, Dewei Yi   +4 more
wiley   +1 more source

Identification of Near Geographical Origin of Wolfberries by a Combination of Hyperspectral Imaging and Multi-Task Residual Fully Convolutional Network

Foods, 2022
Ningxia wolfberry is the only wolfberry product with medicinal value in China. However, the nutritional elements, active ingredients, and economic value of the wolfberry vary considerably among different origins in Ningxia.
Jiarui Cui, Kenken Li, Jie Hao, Fujia Dong, Songlei Wang, A. Rodas-González, Zhifeng Zhang, Haifeng Li, Kangning Wu   +8 more
semanticscholar   +1 more source

A New Parallel Dual-Channel Fully Convolutional Network Via Semi-Supervised FCM for PolSAR Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
Convolutional neural network (CNN) has achieved remarkable success in polarimetric synthetic aperture radar (PolSAR) image classification. However, the PolSAR image classification is a pixelwise prediction assignment.
Feng Zhao, Min Tian, Wen Xie, Hanqiang Liu   +3 more
doaj   +1 more source

A Deep Learning Time Series Approach for Leaf and Wood Classification from Terrestrial LiDAR Point Clouds

Remote Sensing, 2022
The accurate separation between leaf and woody components from terrestrial laser scanning (TLS) data is vital for the estimation of leaf area index (LAI) and wood area index (WAI).
Tao Han, Gerardo Arturo Sánchez-Azofeifa   +1 more
doaj   +1 more source

Classification of cow behavior patterns using inertial measurement units and a fully convolutional network model.

Journal of Dairy Science, 2022
In this study, we aimed to classify 7 cow behavior patterns automatically with an inertial measurement unit (IMU) using a fully convolutional network (FCN) algorithm.
Mei-Qi Liu, Yiqi Wu, Guangyang Li, Mei-Qi Liu, R. Hu, H. Zou, Zhi-Sheng Wang, Ying-Qi Peng   +7 more
semanticscholar   +1 more source

Accuracy (PA), precision (mIoU), and consistency (Kappa) obtained by testing using different backbones in the fully convolutional neural network (FCN).

, 2023
Accuracy (PA), precision (mIoU), and consistency (Kappa) obtained by testing using different backbones in the fully convolutional neural network (FCN).
Guangjie Liu (141451), Jinlong Zhu (796055), Qi Wang (22418), Haotong Hong (16698957)   +3 more
core   +1 more source