News

IEEE1d
A Novel Approach to Identify Diabetic Macular Edema Using a Minimal CNN Model - IEEE Xplore
DME ranks among the primary factors behind the decline in eyesight among individuals with diabetes, and Prompt identification can aid in avoiding irreversible damage. However, current DME detection ...
IEEE3d
Modulation Recognition of Radar Signal Based on an Improved CNN Model - IEEE Xplore
In order to further improve the performance of radar signal modulation recognition, the radar signal modulation recognition algorithm based on an improved convolutional neural networks (CNN) model is ...
IEEE4d
A Novel Approach to Wireless Network Traffic Prediction using CNN-LSTM Attention Model with Prophet Model - IEEE Xplore
This paper presents a novel methodology for predicting network traffic in complex and dynamic environments. In order to tackle the difficulties associated with precise forecasting of network traffic ...
IEEE5d
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning - IEEE Xplore
Remarkable progress has been made in image recognition, primarily due to the availability of large-scale annotated datasets and deep convolutional neural networks (CNNs). CNNs enable learning ...
IEEE5d
A CNN-LSTM Model for Sleep Stage Scoring Using EEG Signals
This paper proposes a deep-learning model for automated sleep stage scoring with single-channel EEG recordings that combines CNN and LSTM. Several of the methods in use today rely on qualities that ...
IEEE5d
Face Image Scanning for Differentiation of Child/Adult images using a CNN-Based Model - IEEE Xplore
Differentiating child and adult images is a crucial requirement for many applications. This paper proposes an approach using a Convolutional Neural Network (CNN) model to distinguish between ...
IEEE5d
A Multi-Channel Feature Fusion CNN-Bi-LSTM Epilepsy EEG Classification and Prediction Model Based on Attention Mechanism - IEEE Xplore
Epilepsy is the unstable state caused by excessive discharge of brain cells. In more than 30 percent of epilepsy cases, seizures cannot be controlled with medication or surgery. Refractory epilepsy ...
IEEE6d
Using Fuzzy Mask R-CNN Model to Automatically Identify Tomato Ripeness - IEEE Xplore
Manual inspection and harvesting of ripening tomatoes is time consuming and labor intensive. Smart agriculture can emphasize the use of digital horticultural resources for farming and can increase ...