Results 1 to 10 of about 93,755 (115)
A novel fully convolutional network for visual saliency prediction [PDF]
PeerJ Computer Science, 2020 A human Visual System (HVS) has the ability to pay visual attention, which is one of the many functions of the HVS. Despite the many advancements being made in visual saliency prediction, there continues to be room for improvement.
Bashir Muftah Ghariba +2 more
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RatLesNetv2: A Fully Convolutional Network for Rodent Brain Lesion Segmentation [PDF]
Frontiers in Neuroscience, 2020 We present a fully convolutional neural network (ConvNet), named RatLesNetv2, for segmenting lesions in rodent magnetic resonance (MR) brain images. RatLesNetv2 architecture resembles an autoencoder and it incorporates residual blocks that facilitate its
Juan Miguel Valverde +7 more
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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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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
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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
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Parallel Fully Convolutional Network for Semantic Segmentation
IEEE Access, 2021 Fully convolutional networks (FCNs) have been widely applied for dense classification tasks such as semantic segmentation. As a large number of works based on FCNs are proposed, various semantic segmentation models have been improved significantly ...
Jian Ji +5 more
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Susceptibility-Guided Landslide Detection Using Fully Convolutional Neural Network
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Automatic landslide detection based on very high spatial resolution remote sensing images is crucial for disaster prevention and mitigation applications.
Yangyang Chen +7 more
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FaceDetectNet: face detection via fully-convolutional network [PDF]
Компьютерная оптика, 2019 Face detection is one of the most popular computer vision tasks. There are a lot of face detection approaches proposed including different CNN-based techniques, but the problem of optimal balancing between detection quality and computational speed is ...
Vladimir Gorbatsevich +2 more
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Biomolecules, 2021 Identifying localization of proteins and their specific subpopulations associated with certain cellular compartments is crucial for understanding protein function and interactions with other macromolecules. Fluorescence microscopy is a powerful method to
Kaisa Liimatainen +3 more
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Shape Carving Methods of Geologic Body Interpretation from Seismic Data Based on Deep Learning
Energies, 2022 The task of seismic data interpretation is a time-consuming and uncertain process. Machine learning tools can help to build a shortcut between raw seismic data and reservoir characteristics of interest. Recently, techniques involving convolutional neural
Sergei Petrov +3 more
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