Results 11 to 20 of about 18,989 (190)

AdaFI-FCN: an adaptive feature integration fully convolutional network for predicting driver’s visual attention

Geo-spatial Information Science, 2022
Visual Attention Prediction (VAP) is widely applied in GIS research, such as navigation task identification and driver assistance systems. Previous studies commonly took color information to detect the visual saliency of natural scene images. However, these studies rarely considered adaptively feature integration to different geospatial scenes in ...
Bowen Shi, Weihua Dong, Zhicheng Zhan
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FCN-Attention: A deep learning UWB NLOS/LOS classification algorithm using fully convolution neural network with self-attention mechanism

Geo-spatial Information Science, 2023
The Ultra-Wideband (UWB) Location-Based Service is receiving more and more attention due to its high ranging accuracy and good time resolution. However, the None-Line-of-Sight (NLOS) propagation may reduce the ranging accuracy for UWB localization system in indoor environment.
Yu Pei, Ruizhi Chen, Deren Li, Xiongwu Xiao, Xingyu Zheng   +4 more
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Comparison of Fully Convolutional Networks (FCN) and U-Net for Road Segmentation from High Resolution Imageries

International Journal of Environment and Geoinformatics, 2020
Segmentation is one of the most popular classification techniques which still have semantic labels. In this context, the segmentation of different objects such as cars, airplanes, ships, and buildings that are independent of background and objects such as land use and vegetation classes, which are difficult to discriminate from the background is ...
Ozan Öztürk, Batuhan Sarıtürk, Dursun Zafer Şeker   +2 more
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R-FCN++: Towards Accurate Region-Based Fully Convolutional Networks for Object Detection

Proceedings of the AAAI Conference on Artificial Intelligence, 2018
Region based detectors like Faster R-CNN and R-FCN have achieved leading performance on object detection benchmarks. However, in Faster R-CNN, RoI pooling is used to extract feature of each region, which might harm the classification as the RoI pooling loses spatial resolution.
Zeming Li, Yilun Chen, Gang Yu, Yangdong Deng   +3 more
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Investigasi Pengaruh Skema Stride dan Step Training untuk Deteksi Jari Pada Region-based Fully Convolutional Network (R-FCN) dalam Teknologi Augmented Reality

Jurnal Ilmiah FIFO, 2021
Abstract  Combining the real world with the virtual world and then modeling it in 3D is an effort carried on Augmented Reality (AR) technology. Using fingers for computer operations on multi-devices makes the system more interactive. Marker-based AR is one type of AR that uses markers in its detection.
Hashfi Fadhillah, Suryo Adhi Wibowo, Rita Purnamasari   +2 more
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On Study of the Reliable Fully Convolutional Networks with Tree Arranged Outputs (TAO-FCN) for Handwritten String Recognition [PDF]

, 2017
Rejected by ICDAR ...
Song Wang, Jun Sun, Satoshi Naoi
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Multi-phase level set algorithm based on fully convolutional networks (FCN-MLS) for retinal layer segmentation in SD-OCT images with central serous chorioretinopathy (CSC)

Biomedical Optics Express, 2019
As a function of the spatial position of the optical coherence tomography (OCT) image, retinal layer thickness is an important diagnostic indicator for many retinal diseases. Reliable segmentation of the retinal layer is necessary for extracting useful clinical information.
Yanan Ruan, Jie Xue, Tianlai Li, Danhua Liu, Hua Lu, Meirong Chen, Tingting Liu, Sijie Niu, Dengwang Li   +8 more
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Dual-Path Adversarial Learning for Fully Convolutional Network (FCN)-Based Medical Image Segmentation [PDF]

The Visual Computer, 2018
Segmentation of regions of interest (ROIs) in medical images is an important step for image analysis in computer-aided diagnosis systems. In recent years, segmentation methods based on fully convolutional networks (FCNs) have achieved great success in general images.
Lei Bi, Dagan Feng, Jinman Kim
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A residual fully convolutional network (Res-FCN) for electromagnetic inversion of high contrast scatterers at an arbitrary frequency within a wide frequency band [PDF]

Inverse Problems
Abstract Many successful machine learning methods have been developed for electromagnetic (EM) inverse scattering problems. However, so far, their inversion has been performed only at the specifically trained frequencies. To make the machine learning based inversion method more generalizable for realistic engineering applications, this ...
Hao-Jie Hu, Jiawen Li, Li‐Ye Xiao, Yu Cheng, Qing Liu   +4 more
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ADVANCEMENTS IN SEMANTIC SEGMENTATION: A COMPREHENSIVE REVIEW AND COMPARATIVE ANALYSIS OF FULLY CONVOLUTIONAL NETWORKS (FCN)

International Research Journal of Modernization in Engineering Technology and Science
Shoury Verma, Vaibhav Saini, Vivek Singh, R Girshick, J Donahue, T Darrell, J Malik, S Gupta, P Arbelaez, J Malik, S Gupta, R Girshick, P Arbelaez, J Malik, B Hariharan, P Arbelaez, L Bourdev, S Maji, J Malik, B Hariharan, P Arbelaez, R Girshick, J Malik, K He, X Zhang, S Ren, J Sun   +26 more
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