[HTML][HTML] Recurrent neural networks: A comprehensive review of architectures, variants, and applications
Recurrent neural networks (RNNs) have significantly advanced the field of machine learning
(ML) by enabling the effective processing of sequential data. This paper provides a …
(ML) by enabling the effective processing of sequential data. This paper provides a …
Trends in using deep learning algorithms in biomedical prediction systems
Y Wang, L Liu, C Wang - Frontiers in Neuroscience, 2023 - frontiersin.org
In the domain of using DL-based methods in medical and healthcare prediction systems, the
utilization of state-of-the-art deep learning (DL) methodologies assumes paramount …
utilization of state-of-the-art deep learning (DL) methodologies assumes paramount …
Delineating the spatial-temporal variation of air pollution with urbanization in the Belt and Road Initiative area
The rapid urbanization in the Belt and Road Initiative (BRI) area has aggravated the cross-
regional pollution of PM 2.5 and aroused concern about the conflicts between urban …
regional pollution of PM 2.5 and aroused concern about the conflicts between urban …
Topic modeling and sentiment analysis of online education in the COVID-19 era using social networks based datasets
Sentiment Analysis (SA) is a technique to study people's attitudes related to textual data
generated from sources like Twitter. This study suggested a powerful and effective technique …
generated from sources like Twitter. This study suggested a powerful and effective technique …
Two-path deep semisupervised learning for timely fake news detection
News in social media, such as Twitter, has been generated in high volume and speed.
However, very few of them are labeled (as fake or true news) by professionals in near real …
However, very few of them are labeled (as fake or true news) by professionals in near real …
[HTML][HTML] Integrating domain knowledge for biomedical text analysis into deep learning: A survey
The past decade has witnessed an explosion of textual information in the biomedical field.
Biomedical texts provide a basis for healthcare delivery, knowledge discovery, and decision …
Biomedical texts provide a basis for healthcare delivery, knowledge discovery, and decision …
Deep learning for medicinal plant species classification and recognition: a systematic review
AK Mulugeta, DP Sharma, AH Mesfin - Frontiers in Plant Science, 2024 - frontiersin.org
Knowledge of medicinal plant species is necessary to preserve medicinal plants and
safeguard biodiversity. The classification and identification of these plants by botanist …
safeguard biodiversity. The classification and identification of these plants by botanist …
A review of Chinese named entity recognition.
Abstract Named Entity Recognition (NER) is used to identify entity nouns in the corpus such
as Location, Person and Organization, etc. NER is also an important basic of research in …
as Location, Person and Organization, etc. NER is also an important basic of research in …
Named-entity recognition for a low-resource language using pre-trained language model
HM Yohannes, T Amagasa - Proceedings of the 37th ACM/SIGAPP …, 2022 - dl.acm.org
This paper proposes a method for Named-Entity Recognition (NER) for a low-resource
language, Tigrinya, using a pre-trained language model. Tigrinya is a morphologically rich …
language, Tigrinya, using a pre-trained language model. Tigrinya is a morphologically rich …
Sharing to learn and learning to share--Fitting together Meta-Learning, Multi-Task Learning, and Transfer Learning: A meta review
Integrating knowledge across different domains is an essential feature of human learning.
Learning paradigms such as transfer learning, meta learning, and multi-task learning reflect …
Learning paradigms such as transfer learning, meta learning, and multi-task learning reflect …