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CNN-RNN based intelligent recommendation for online medical pre-diagnosis support
The rapidly developed Health 2.0 technology has provided people with more opportunities
to conduct online medical consultation than ever before. Understanding contexts within …
to conduct online medical consultation than ever before. Understanding contexts within …
Network intrusion detection combined hybrid sampling with deep hierarchical network
K Jiang, W Wang, A Wang, H Wu - IEEE access, 2020 - ieeexplore.ieee.org
Intrusion detection system (IDS) plays an important role in network security by discovering
and preventing malicious activities. Due to the complex and time-varying network …
and preventing malicious activities. Due to the complex and time-varying network …
Bi-directional long short-term memory method based on attention mechanism and rolling update for short-term load forecasting
S Wang, X Wang, S Wang, D Wang - … Journal of Electrical Power & Energy …, 2019 - Elsevier
Short-term load forecasting (STLF) plays an important role in the planning and operation of
power systems. However, with the wide use of distributed generations (DGs) and smart …
power systems. However, with the wide use of distributed generations (DGs) and smart …
A novel multi-module integrated intrusion detection system for high-dimensional imbalanced data
J Cui, L Zong, J **e, M Tang - Applied Intelligence, 2023 - Springer
The high dimension, complexity, and imbalance of network data are hot issues in the field of
intrusion detection. Nowadays, intrusion detection systems face some challenges in …
intrusion detection. Nowadays, intrusion detection systems face some challenges in …
Deep sequence to sequence Bi-LSTM neural networks for day-ahead peak load forecasting
N Mughees, SA Mohsin, A Mughees… - Expert Systems with …, 2021 - Elsevier
The power industry is currently facing the problem of an electricity supply–demand
imbalance. The most inexpensive and efficient solution to alleviate this imbalance is to …
imbalance. The most inexpensive and efficient solution to alleviate this imbalance is to …
Speaker gender recognition based on deep neural networks and ResNet50
Several speaker recognition algorithms failed to get the best results because of the wildly
varying datasets and feature sets for classification. Gender information helps reduce this …
varying datasets and feature sets for classification. Gender information helps reduce this …
Speech2face: Learning the face behind a voice
How much can we infer about a person's looks from the way they speak? In this paper, we
study the task of reconstructing a facial image of a person from a short audio recording of …
study the task of reconstructing a facial image of a person from a short audio recording of …
[HTML][HTML] Age and gender recognition using a convolutional neural network with a specially designed multi-attention module through speech spectrograms
Speech signals are being used as a primary input source in human–computer interaction
(HCI) to develop several applications, such as automatic speech recognition (ASR), speech …
(HCI) to develop several applications, such as automatic speech recognition (ASR), speech …
Multimodal age and gender estimation for adaptive human-robot interaction: A systematic literature review
Identifying the gender of a person and his age by way of speaking is considered a crucial
task in computer vision. It is a very important and active research topic with many areas of …
task in computer vision. It is a very important and active research topic with many areas of …
[HTML][HTML] SPIDER: A shallow PCA based network intrusion detection system with enhanced recurrent neural networks
In recent years, ensuring the stability of the huge volume of data generated by billions of
users has become the main concern in the field of cyber security. Network security is an …
users has become the main concern in the field of cyber security. Network security is an …