Search Results for author:
Found 14 papers, 0 papers with code
Deep Learning for Size and Microscope Feature Extraction and Classification in Oral Cancer: Enhanced Convolution Neural Network
Conclusion: The proposed system focuses on the accurate classification of oral cancer cells of different anatomical locations from the CLE images.
Deep Learning Neural Network for Lung Cancer Classification: Enhanced Optimization Function
The aim of this work is to increase the overall prediction accuracy along with reducing processing time by using multispace image in pooling layer of convolution neural network.
A novel solution of deep learning for enhanced support vector machine for predicting the onset of type 2 diabetes
The proposed system consists of a deep learning technique that uses the Support Vector Machine (SVM) algorithm along with the Radial Base Function (RBF) along with the Long Short-term Memory Layer (LSTM) for prediction of onset of Type 2 Diabetes.
A Novel Enhanced Convolution Neural Network with Extreme Learning Machine: Facial Emotional Recognition in Psychology Practices
The simulation results show significant improvements in accuracy and processing time, making the model suitable for the video analysis process.
Deep Learning Neural Networks for Emotion Classification from Text: Enhanced Leaky Rectified Linear Unit Activation and Weighted Loss
The proposed solution improves accuracy and reduces the processing time of text emotion classification.
Deep Learning for Sleep Stages Classification: Modified Rectified Linear Unit Activation Function and Modified Orthogonal Weight Initialisation
Methodology: The proposed system used a modified Orthogonal Convolutional Neural Network and a modified Adam optimisation technique to improve the sleep stage classification accuracy and reduce the gradient saturation problem that occurs due to sigmoid activation function.
Generative Adversarial Network (GAN) and Enhanced Root Mean Square Error (ERMSE): Deep Learning for Stock Price Movement Prediction
It seems that the proposed system concentrates on minimizing the root mean square error and processing time and improving the direction prediction accuracy, and provides a better result in the accuracy of the stock index.
Mixed Reality using Illumination-aware Gradient Mixing in Surgical Telepresence: Enhanced Multi-layer Visualization
The aim of this work is to propose a solution to improve the visualization in the final merged video by producing globally consistent videos when the intensity of illumination in the input source and target video varies.
A Novel Solution of an Elastic Net Regularization for Dementia Knowledge Discovery using Deep Learning
Methodology: The proposed system consists of Convolutional Neural Network (CNN) to enhance the accuracy of classification and prediction by using Elastic Net Regularization.
A Review-based Taxonomy for Secure Health Care Monitoring: Wireless Smart Cameras
The proposed model has been developed for access control to data through the authentication of users in healthcare to reduce data manipulation or theft.
Deep Learning for Breast Cancer Classification: Enhanced Tangent Function
Methodology: The proposed system consists of a Deep Convolutional Neural Network (DCNN) that helps in enhancing and increasing the accuracy of the classification process.
Deep Learning for Vision-Based Fall Detection System: Enhanced Optical Dynamic Flow
This research aims to propose a vision-based fall detection system that improves the accuracy of fall detection in some complex environments such as the change of light condition in the room.
A Novel Solution of Using Mixed Reality in Bowel and Oral and Maxillofacial Surgical Telepresence: 3D Mean Value Cloning algorithm
The purpose of the proposed solution is to decrease the processing time and enhance the accuracy of merged video by decreasing the overlay and visualization error and removing occlusion and artefacts.
A Novel Visualization System of Using Augmented Reality in Knee Replacement Surgery: Enhanced Bidirectional Maximum Correntropy Algorithm
This has led to improve the processing time as well.
