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Ensemble based fully convolutional transformer network for time series classification
Currently, multivariate time series classification is widely used in various fields, including industrial process control, action recognition, and...
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SRFCNM: Spatiotemporal recurrent fully convolutional network model for salient object detection
Video saliency detection has recently been widely used because of its ability to distinguish significant regions of interest. It has several...
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Multispecies bird sound recognition using a fully convolutional neural network
This study proposes a method based on fully convolutional neural networks (FCNs) to identify migratory birds from their songs, with the objective of...
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A two-stage attention augmented fully convolutional network-based dynamic video summarization
Video summarization deals with the generation of a condensed version of a video by retaining the important information while eliminating redundant...
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Multi-atlas subcortical segmentation: an orchestration of 3D fully convolutional network and generalized mixture function
To accurately segment subcortical structures and therefore profit for numerous neuroimaging applications, we proposed a multi-atlas subcortical...
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Image forgery localization based on fully convolutional network with noise feature
To detect the maliciously tampered region in digital images, this paper proposes an image forgery localization method based on a fully convolutional...
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IFAS: improved fully automatic segmentation convolutional neural network model along with morphological segmentation for brain tumor detection
Image segmentation of brain Magnetic Resonance Imaging (MRI) images is one of the trusted method for tumor detection. The tumors are dynamically...
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Analytical Calculation of Weights Convolutional Neural Network
AbstractIn this paper proposes an algorithm for the analytical calculation of convolutional neural networks without using neural network training...
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Fully convolutional network for automated detection and diagnosis of mammographic masses
Breast cancer, though rare in male, is very frequent in female and has high mortality rate which can be reduced if detected and diagnosed at the...
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Fully convolutional neural network with attention gate and fuzzy active contour model for skin lesion segmentation
This study proposes an approach for segmentation of skin lesions from dermoscopic images based on fully convolutional neural network and active...
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Traversability Learning from Aerial Images with Fully Convolutional Neural Networks
Traversability analysis is essential for ground robot operations because it allows the incorporation of knowledge about traversable and...
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Dependency-position relation graph convolutional network with hierarchical attention mechanism for relation extraction
Existing research extensively incorporates syntactic information, especially dependency trees, to enhance the performance of relation extraction...
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Amplitude transformed quantum convolutional neural network
With the rapid development of quantum neural networks (QNN), several quantum simulations of convolutional neural networks (CNN) have been proposed....
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A multimodal attention-fusion convolutional neural network for automatic detection of sleep disorders
Sleep is essential for human physical and mental health. Sleep disorders are a significant threat to human health, and a large number of people in...
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Convolutional network fabric pruning with label noise
This paper presents an iterative pruning strategy for Convolutional Network Fabrics (CNF) in presence of noisy training and testing data. With the...
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OmiQnet: Multiscale feature aggregation convolutional neural network for omnidirectional image assessment
Recently, deep learning-based methods for quality assessment of omnidirectional images (OIs) have gained widespread attention. However, existing...
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Fully convolutional neural networks for LIDAR–camera fusion for pedestrian detection in autonomous vehicle
Pedestrian detection appears to be an integral part of a vast array of vision-based technologies, ranging from item recognition and monitoring via...
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Contact classification for human–robot interaction with densely connected convolutional neural network and convolutional block attention module
Human–robot interaction (HRI) is a challenging topic to perform various tasks in many repetitive and dangerous tasks. However, humans not only share...
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Adaptive spatio-temporal graph convolutional network with attention mechanism for mobile edge network traffic prediction
In the current era of mobile edge networks, a significant challenge lies in overcoming the limitations posed by limited edge storage and...
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A two-stage segmentation of sublingual veins based on compact fully convolutional networks for Traditional Chinese Medicine images
As one of the key methods of Traditional Chinese Medicine inspection, tongue diagnosis manifests the advantages of simplicity and directness....
