Toward Smart Healthcare: Challenges and Opportunities in IoT and ML
M Saifuzzaman, TN Ananna - IoT and ML for Information Management: A …, 2024 - Springer
The COVID-19 pandemic and other ongoing health crises have underscored the need for
prompt healthcare services worldwide. The traditional healthcare system, centered around …
prompt healthcare services worldwide. The traditional healthcare system, centered around …
Face anti-spoofing via jointly modeling local texture and constructed depth
L Li, Z Yao, S Gao, H Han, Z Xia - Engineering Applications of Artificial …, 2024 - Elsevier
To solve the security problem posed by fake face presentation attacks in face recognition
systems, many detection methods have been proposed in recent years. Among these …
systems, many detection methods have been proposed in recent years. Among these …
Exploring temperature-dependent photoluminescence dynamics of colloidal CdSe nanoplatelets using machine learning approach
IP Malashin, D Daibagya, V Tynchenko, V Nelyub… - Scientific Reports, 2024 - nature.com
The study explore machine learning (ML) techniques to predict temperature-dependent
photoluminescence (PL) spectra in colloidal CdSe nanoplatelets (NPLs), leveraging …
photoluminescence (PL) spectra in colloidal CdSe nanoplatelets (NPLs), leveraging …
SaPt-CNN-LSTM-AR-EA: a hybrid ensemble learning framework for time series-based multivariate DNA sequence prediction
W Yan, L Tan, L Meng-Shan, S Sheng, W Jun, W Fu-An - PeerJ, 2023 - peerj.com
Biological sequence data mining is hot spot in bioinformatics. A biological sequence can be
regarded as a set of characters. Time series is similar to biological sequences in terms of …
regarded as a set of characters. Time series is similar to biological sequences in terms of …
Advancing Stock Market Predictions with Time Series Analysis Including LSTM and ARIMA
Predicting stock market prices accurately is a major task for investors and traders seeking to
optimize their decision-making processes. This research focuses on the comparative …
optimize their decision-making processes. This research focuses on the comparative …
[引用][C] Enhancing Time-Series Classification with InceptionResNet: Integrating Deep Learning Techniques for Improved Performance
NT Dang, ND Chau, VT Thai Linh, DH Minh… - Vietnam Journal of …, 2024 - World Scientific
In the domain of deep learning, several architectures have been extensively used for time
series data analysis and mining, including recurrent neural network (RNN)-based …
series data analysis and mining, including recurrent neural network (RNN)-based …
[引用][C] A Hybrid Neural Network-Based Fast Financial Fraud Detection Model
Z Zheng, R Zhang, Y Li, X Huang… - Journal of Circuits …, 2024 - World Scientific
With the increasing number of financial transactions, financial fraud has become
increasingly serious for financial institutions and the public. The core idea of this model is to …
increasingly serious for financial institutions and the public. The core idea of this model is to …
[引用][C] Predicting and diagnosis of COVID-19 based on IoT and machine learning algorithm
F Ertam, IF Kilincer - 2024 - Elsevier