A survey of machine learning and deep learning in remote sensing of geological environment: Challenges, advances, and opportunities
Due to limited resources and environmental pollution, monitoring the geological
environment has become essential for many countries' sustainable development. As various …
environment has become essential for many countries' sustainable development. As various …
A survey on heterogeneous graph embedding: methods, techniques, applications and sources
Heterogeneous graphs (HGs) also known as heterogeneous information networks have
become ubiquitous in real-world scenarios; therefore, HG embedding, which aims to learn …
become ubiquitous in real-world scenarios; therefore, HG embedding, which aims to learn …
[HTML][HTML] Bidirectional convolutional recurrent neural network architecture with group-wise enhancement mechanism for text sentiment classification
A Onan - Journal of King Saud University-Computer and …, 2022 - Elsevier
Sentiment analysis has been a well-studied research direction in computational linguistics.
Deep neural network models, including convolutional neural networks (CNN) and recurrent …
Deep neural network models, including convolutional neural networks (CNN) and recurrent …
Graph neural networks: foundation, frontiers and applications
The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …
recent years. Graph neural networks, also known as deep learning on graphs, graph …
Unified named entity recognition as word-word relation classification
So far, named entity recognition (NER) has been involved with three major types, including
flat, overlapped (aka. nested), and discontinuous NER, which have mostly been studied …
flat, overlapped (aka. nested), and discontinuous NER, which have mostly been studied …
A unified generative framework for various NER subtasks
Named Entity Recognition (NER) is the task of identifying spans that represent entities in
sentences. Whether the entity spans are nested or discontinuous, the NER task can be …
sentences. Whether the entity spans are nested or discontinuous, the NER task can be …
Arabert: Transformer-based model for arabic language understanding
The Arabic language is a morphologically rich language with relatively few resources and a
less explored syntax compared to English. Given these limitations, Arabic Natural Language …
less explored syntax compared to English. Given these limitations, Arabic Natural Language …
Domain-specific knowledge graphs: A survey
B Abu-Salih - Journal of Network and Computer Applications, 2021 - Elsevier
Abstract Knowledge Graphs (KGs) have made a qualitative leap and effected a real
revolution in knowledge representation. This is leveraged by the underlying structure of the …
revolution in knowledge representation. This is leveraged by the underlying structure of the …
Occupancy prediction using deep learning approaches across multiple space types: A minimum sensing strategy
The proliferation of sensing technologies has allowed the collection of occupancy-related
data to support various building applications, including adaptive HVAC and lighting controls …
data to support various building applications, including adaptive HVAC and lighting controls …
Deep reinforcement learning in computer vision: a comprehensive survey
Deep reinforcement learning augments the reinforcement learning framework and utilizes
the powerful representation of deep neural networks. Recent works have demonstrated the …
the powerful representation of deep neural networks. Recent works have demonstrated the …