Results 41 to 50 of about 6,093,681 (207)

Delineation of Agricultural Field Boundaries from Sentinel-2 Images Using a Novel Super-Resolution Contour Detector Based on Fully Convolutional Networks

Remote Sensing, 2019
Boundaries of agricultural fields are important features necessary for defining the location, shape, and spatial extent of agricultural units. They are commonly used to summarize production statistics at the field level. In this study, we investigate the
Khairiya Mudrik Masoud, Claudio Persello, Valentyn A. Tolpekin   +2 more
doaj   +1 more source

Attention Mechanism Cloud Detection With Modified FCN for Infrared Remote Sensing Images

IEEE Access, 2021
Semantic segmentation (SS) has been widely applied for cloud detection (CD) in remote sensing images (RSIs) with high spatial and spectral resolution because of its effective pixel-level feature extraction structure.
Liyuan Li, Xiaoyan Li, Xin Liu, Wenwen Huang, Zhuoyue Hu, Fansheng Chen   +5 more
doaj   +1 more source

Boundary-aware fully convolutional network for brain tumor segmentation [PDF]

, 2017
We propose a novel, multi-task, fully convolutional network (FCN) architecture for automatic segmentation of brain tumor. This network extracts multi-level contextual information by concatenating hierarchical feature representations extracted from ...
Haocheng Shen, Stephen J. McKenna, Zhang, Jianguo, Ruixuan Wang, Jianguo Zhang, Shen, Haocheng, Wang, Ruixuan, McKenna, Stephen J.; id_orcid   +7 more
core   +1 more source

Multilabel Remote Sensing Image Retrieval Based on Fully Convolutional Network

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
Conventional remote sensing image retrieval (RSIR) system usually performs single-label retrieval where each image is annotated by a single label representing the most significant semantic content of the image.
Zhenfeng Shao, Weixun Zhou, Xueqing Deng, Maoding Zhang, Qimin Cheng   +4 more
doaj   +1 more source

Change Detection in Hyperspectral Images Using Recurrent 3D Fully Convolutional Networks

Remote Sensing, 2018
Hyperspectral change detection (CD) can be effectively performed using deep-learning networks. Although these approaches require qualified training samples, it is difficult to obtain ground-truth data in the real world.
Ahram Song, Jaewan Choi, Youkyung Han, Yongil Kim   +3 more
doaj   +1 more source

Augmentation of Deep Learning Models for Multistep Traffic Speed Prediction

Applied Sciences, 2022
Traffic speed prediction is a vital part of the intelligent transportation system (ITS). Predicting accurate traffic speed is becoming an important and challenging task with the rapid development of deep learning and increasing traffic data size. In this
Adnan Riaz, Hameedur Rahman, Muhammad Ali Arshad, Muhammad Nabeel, Affan Yasin, Mosleh Hmoud Al-Adhaileh, Elsayed Tag Eldin, Nivin A. Ghamry   +7 more
doaj   +1 more source

A DEEP LEARNING BASED SURROGATE MODEL FOR ESTIMATING THE FLUX AND POWER DISTRIBUTION SOLVED BY DIFFUSION EQUATION [PDF]

EPJ Web of Conferences, 2021
A deep learning based surrogate model is proposed for replacing the conventional diffusion equation solver and predicting the flux and power distribution of the reactor core. Using the training data generated by the conventional diffusion equation solver,
Zhang Qian, Zhang Jinchao, Liang Liang, Li Zhuo, Zhang Tengfei   +4 more
doaj   +1 more source

Fully convolutional neural network for Malaysian road lane detection [PDF]

, 2018
Recently, a deep learning, Fully Convolutional Neural Network (FCN) has been widely studied because it can demonstrate promising results in the application of detection of objects in an image or video.
Ariff, M. H., Zakaria, N. J., Hassan, N., Zamzuri, H., Saruchi, S. A., Shapiai, M. I.   +5 more
core   +1 more source

Automatic Building Segmentation of Aerial Imagery Using Multi-Constraint Fully Convolutional Networks

Remote Sensing, 2018
Automatic building segmentation from aerial imagery is an important and challenging task because of the variety of backgrounds, building textures and imaging conditions.
Guangming Wu, Xiaowei Shao, Zhiling Guo, Qi Chen, Wei Yuan, Xiaodan Shi, Yongwei Xu, Ryosuke Shibasaki   +7 more
doaj   +1 more source

A Plankton Detection Method Based on Neural Networks and Digital Holographic Imaging

Chemosensors, 2022
Detecting marine plankton by means of digital holographic microscopy (DHM) has been successfully deployed in recent decades; however, in most previous studies, the identification of the position, shape, and size of plankton has been neglected, which may ...
Kaiqi Lang, Hui Cai, Xiaoping Wang
doaj   +1 more source