Offline arabic handwriting recognition using deep machine learning: A review of recent advances
In pattern recognition, automatic handwriting recognition (AHWR) is an area of research that
has developed rapidly in the last few years. It can play a significant role in broad-spectrum of …
has developed rapidly in the last few years. It can play a significant role in broad-spectrum of …
Novel deep convolutional neural network-based contextual recognition of Arabic handwritten scripts
Offline Arabic Handwriting Recognition (OAHR) has recently become instrumental in the
areas of pattern recognition and image processing due to its application in several fields …
areas of pattern recognition and image processing due to its application in several fields …
A ranking-based feature selection approach for handwritten character recognition
Feature selection is generally considered a very important step in any pattern recognition
process. Its aim is that of reducing the computational cost of the classification task, in an …
process. Its aim is that of reducing the computational cost of the classification task, in an …
Deep learning in cervical cancer diagnosis: architecture, opportunities, and open research challenges
N Youneszade, M Marjani, CP Pei - IEEE Access, 2023 - ieeexplore.ieee.org
Nowadays, deep learning (DL) is a popular tool used in various applications in different
fields, including the medical domain. DL techniques can cope with several challenges …
fields, including the medical domain. DL techniques can cope with several challenges …
Advances in the modeling of multiphase flows and their application in nuclear engineering—A review
M Wu, J Zhang, N Gui, Q Zou, X Yang, J Tu… - Experimental and …, 2024 - Springer
This paper mainly reviews the research progress on multiphase flow in nuclear engineering.
This paper is composed of three parts. The first part documents a literature statistical …
This paper is composed of three parts. The first part documents a literature statistical …
An efficient framework for heart disease classification using feature extraction and feature selection technique in data mining
In the classification of the heart disease data set a high dimensional data set is used in the
pre processing stage of data mining process. This raw dataset consist of redundant and …
pre processing stage of data mining process. This raw dataset consist of redundant and …
[HTML][HTML] Self-supervised learning-based two-phase flow regime identification using ultrasonic sensors in an S-shape riser
Two-phase flow regime identification is an essential transdisciplinary topic that spans digital
signal processing, artificial intelligence, chemical engineering, and energy. Multiphase flow …
signal processing, artificial intelligence, chemical engineering, and energy. Multiphase flow …
OCR-nets: variants of pre-trained CNN for Urdu handwritten character recognition via transfer learning
Deep Convolutional neural networks (CNN) have been among the utmost competitive
neural network architectures and have set the state-of-the-art in various fields of computer …
neural network architectures and have set the state-of-the-art in various fields of computer …
Comparing filter and wrapper approaches for feature selection in handwritten character recognition
It is generally agreed that the selection of an appropriate set of features is a fundamental
process in the development of any pattern recognition system. Its purpose is to identify the …
process in the development of any pattern recognition system. Its purpose is to identify the …
Prediction of heart disease using artificial neural network
Heart disease is increasing rapidly due to number of reasons. If we predict cardiac arrest
(dangerous conditions of heart) in the early stages, it will be very helpful to cured this …
(dangerous conditions of heart) in the early stages, it will be very helpful to cured this …