Results 21 to 30 of about 6,093,681 (207)
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 +1 more
doaj +1 more source
sagieppel/Fully-convolutional-neural-network-FCN-for-semantic-segmentation-with-pytorch: 1.0
, 2021 <p>1</p ...
sagieppel
core +1 more source
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 0004 +2 more
openaire +2 more sources
Time series classification based on statistical features
EURASIP Journal on Wireless Communications and Networking, 2020 This paper presents a statistical feature approach in fully convolutional time series classification (TSC), which is aimed at improving the accuracy and efficiency of TSC.
Yuxia Lei, Zhongqiang Wu
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Feature extraction from satellite images using segnet and fully convolutional networks (FCN)
International Journal of Engineering and Geosciences, 2020 Object detection and classification are among the most popular topics in Photogrammetry and Remote Sensing studies. With technological developments, a large number of high-resolution satellite images have been obtained and it has become possible to distinguish many different objects.
Batuhan SARİTURK +3 more
openaire +5 more sources
Optimization of Fully Convolutional Network for Road Safety Attribute Detection
, 2021 Even though, deep learning techniques demonstrate an outstanding performance in various applications, success of deep learning techniques depends upon appropriately setting their parameters in achieving most accurate results.
Sanjeewani, Pubudu +5 more
core +1 more source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Fully convolutional network (FCN), which has excellent capability for capturing spatial context, was introduced to improve the performance of hyperspectral image classification (HSIC).
Xueliang Zhang +4 more
doaj +1 more source
LSTM Fully Convolutional Networks for Time Series Classification
IEEE Access, 2018 Fully convolutional neural networks (FCNs) have been shown to achieve the state-of-the-art performance on the task of classifying time series sequences.
Fazle Karim +3 more
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, 2023 Accuracy (PA), precision (mIoU), and consistency (Kappa) obtained by testing using different backbones in the fully convolutional neural network (FCN).
Guangjie Liu (141451) +3 more
core +1 more source
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
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