The manufacturing and dissemination of spores is the main purpose of sporocarps which is the specialized type of configuration found in freshwater plants of the Salviniales family. Though sporocarp are mainly used for...
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In this paper,we address the problem of unsuperised social network embedding,which aims to embed network nodes,including node attributes,into a latent low dimensional *** recent methods,the fusion mechanism of node at...
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In this paper,we address the problem of unsuperised social network embedding,which aims to embed network nodes,including node attributes,into a latent low dimensional *** recent methods,the fusion mechanism of node attributes and network structure has been proposed for the problem and achieved impressive prediction ***,the non-linear property of node attributes and network structure is not efficiently fused in existing methods,which is potentially helpful in learning a better network *** this end,in this paper,we propose a novel model called ASM(Adaptive Specific Mapping)based on encoder-decoder *** encoder,we use the kernel mapping to capture the non-linear property of both node attributes and network *** particular,we adopt two feature mapping functions,namely an untrainable function for node attributes and a trainable function for network *** the mapping functions,we obtain the low dimensional feature vectors for node attributes and network structure,***,we design an attention layer to combine the learning of both feature vectors and adaptively learn the node *** encoder,we adopt the component of reconstruction for the training process of learning node attributes and network *** conducted a set of experiments on seven real-world social network *** experimental results verify the effectiveness and efficiency of our method in comparison with state-of-the-art baselines.
In recent decades, Cellular Networks (CN) have been used broadly in communication technologies. The most critical challenge in the CN was congestion control due to the distributed mobile environment. Some approaches, ...
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A novel energy-efficient clustering-based congestion-awareness routing mechanism has been developed for wireless sensor network (WSN). In the first stage, some set of sensor nodes are initialised in the WSN environmen...
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The recognition and categorization of butterflies is crucial for the preservation of butterfly species in the fields of entomology, computer vision and deep learning. Environmentalists have long utilized butterflies a...
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Effective anomaly detection in unlabeled datasets is crucial for numerous applications across different domains. This paper presents a novel methodology for one-class anomaly detection that leverages unsupervised lear...
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Sign language recognition is an important social issue to be addressed which can benefit the deaf and hard of hearing community by providing easier and faster communication. Some previous studies on sign language reco...
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Classification of brain haemorrhage is a challenging task that needs to be solved to help advance medical treatment. Recently, it has been observed that efficient deep learning architectures have been developed to det...
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Developing manufacturing methods for flexible electronics will enable and improve the large-scale production of flexible, spatially efficient, and lightweight devices. Laser sintering is a promising postprocessing met...
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Anaemia, a condition characterised by reduced haemoglobin levels, exerts a significant global impact, affecting billions of individuals worldwide. According to data from the World Health Organisation (WHO), India exhi...
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