I-manager's Journal on Image Processing

17/05/2023

Here's a step by step guide to publishing your papers in i-manager's Journals

https://www.youtube.com/watch?v=VXPko9Mq5hY

This video Explains how to Publish your Journals in i-manager's Publications

03/05/2023

i-manager Publications is pleased to be the Publishing Partner of organized by College of Engineering and Technology, University of Technology and Applied Sciences, Nizwa, Oman in collaboration with IEEE Oman section. Nizwa UTAS IEEE-Oman

27/04/2023

i-manager's Journal on Image Processing (JIP)
Volume 10 Issue 1 January - March 2023
Paper: 5
Title: A Review on Glaucoma Detection using Deep Learning Algorithms
Abstract
Glaucoma is a progressive eye condition that causes loss of vision and cannot be restored once it has occurred. The diagnosis of glaucoma is an important issue that has to be resolved in the realm of medicine. There have only been a limited number of research efforts aimed at detecting glaucoma in its earlier stages. Nevertheless, the performance of glaucoma illness identification utilizing the various approaches that are now available was ineffective. In addition to this, the time commitment involved in traditional methods of glaucoma illness identification was significantly higher. Finding glaucoma in color fundus photos is a difficult undertaking that calls both knowledge as well as years of practice. Deep learning techniques have rapidly emerged as a method of choice for the analysis of medical pictures. In this study, we took advantage of the application of various Convolutional Neural Networks (CNN) schemes to demonstrate the influence on performance of relevant factors such as the size of the data set, architecture, and the use of transfer learning versus newly defined architectures at an early stage with higher accuracy and a lower amount of time. Specifically, we compared the two types of architectures in terms of their ability to learn from previous examples. Deep learning techniques have rapidly emerged as a method of choice for the analysis of medical pictures. This study examines the primary deep learning ideas that are applicable to medical image analysis and provides a summary of the contributions to the area. We take a look at the application of deep learning to various image processing tasks such as classification, object identification, segmentation, and registration.
Key words: Deep Learning, Convolutional Neural Network, Glaucoma, Medical Images.

27/04/2023

i-manager's Journal on Image Processing (JIP)
Volume 10 Issue 1 January - March 2023
Paper: 4
Title: A Review on Parkinson's Disease Diagnosis using Machine Learning Techniques
Abstract
The decreased production of dopamine in the forebrain is believed to be the underlying cause of Parkinson's disease, a neurodegenerative disorder that affects the nervous system. Parkinson's disease is a chronic and progressive illness that may develop new symptoms over time (Nilashi et al., 2016). This occurs as neurons in the substantia nigra of the brain gradually die. People with Parkinson's disease may find it difficult to perform everyday tasks in the workplace. Although clinical evaluations consider a significant amount of data that includes various aspects, it is not always easy to determine whether a person has PD based on this data alone. Feature selection methods can help address this issue. Various techniques are being researched, developed, and evaluated for diagnosing Parkinson's disease, based on the relevant information. This study provides an overview of the use of machine learning algorithms to predict Parkinson's disease, as well as the various new technologies that have been developed and the accuracy that has been achieved.
Key words: PD (Parkinson Disease), Dopamine, SVM (Support Vector Machine), KNN (K Nearest Neighbor), ANN (Artificial Neural Network).

27/04/2023

i-manager's Journal on Image Processing (JIP)
Volume 10 Issue 1 January - March 2023
Paper: 3
Title: A Novel Approach for E-Government Services with Artificial Intelligence using CNN
Abstract
Artificial Intelligence (AI) is a domain that works on various complex applications, such as E-government services. In order to provide government services to the people, an online AI-based Deep Learning (DL) model has been developed to check the availability of government schemes. However, several E-government services are not available to the citizens based on their usage. Many challenges have been identified while using E-Government services. This paper introduces the DL model, Convolutional Neural Networks (CNN), to solve the issues in E-Government services. The system focuses on maintaining E-government data resources, and CNN is primarily used to automate E-Government services. Finally, CNN has developed an innovative E-Government environment to support the design, development, and implementation of applications.
Key words: E-Government Services, AI, CNN, Web Services.

27/04/2023

i-manager's Journal on Image Processing (JIP)
Volume 10 Issue 1 January - March 2023
Paper: 2
Title: Breast Cancer Disease Prediction using Ensemble Techniques
Abstract
Breast Cancer is a highly lethal reproductive cancer that disproportionately affects women and is a leading cause of death worldwide. Cancer is characterized by the uncontrolled division and invasion of abnormal cells into the surrounding tissues. Early detection is crucial in the diagnosis of Breast Cancer, as it accounts for a significant percentage of cancer diagnoses and deaths among women. To prevent unnecessary tests, accurate classification of malignant and benign tumors is necessary. Researchers have developed numerous automated classification methods for Breast Cancer, with soft computing techniques being widely used due to their high performance in classification. Machine learning algorithms, known for their ability to identify critical features from medical datasets, are also extensively utilized in Breast Cancer prediction. Therefore, this study seeks to employ Boosting algorithms in machine learning to predict Breast Cancer accurately. Over the years, the mortality rate in Breast Cancer diagnosis has decreased due to research efforts.
Key words: CNN, Deep Learning, SVM, Gradient Boost, XGBoost, AdaBoost.

27/04/2023

i-manager's Journal on Image Processing (JIP)
Volume 10 Issue 1 January - March 2023
Paper: 1
Title: Deep Convolutional Neural Network with a Stochastic Gradient Descent Optimizer (PDCNN-SGD) Model for Telugu Character Recognition
Abstract
Telugu Character Recognition (TCR) has received significant attention because of the drastic increase in technological advancements such as multimedia, smartphones and iPods, and paper documents. Offline character recognition is the process of identifying Telugu characters from the scanned image or document whereas online character recognition enables to recognition of characters by the machine while the user writes. Several researchers have attempted to design online TCR models by the use of distinct classification models and feature extraction approaches. It is still necessary to construct automated and intelligent online TCR models, even if many studies have focused on offline TCR models. The Telugu character dataset construction and validation using an Inception and ResNet-based model are presented. The collection of 645 letters in the dataset includes 18 Achus, 38 Hallus, 35 Othulu, 34*16 Guninthamulu and 10 Ankelu. The proposed technique aims to efficiently recognize and identify distinctive Telugu characters online. This model's main preprocessing steps to achieve its goals include normalization, smoothing, and interpolation. Improved recognition performance can be attained by using Stochastic Gradient Descent (SGD) to optimize the model's hyperparameters.
Key words: Telugu Letter Dataset, Data Preprocessing, Deep Neural Networks, Training and Testing.

27/04/2023

i-manager's Journal on Image Processing (JIP), a double-blind peer-reviewed Journal (Print ISSN: 2349-4530 Online ISSN: 2349-6827)
presents high quality research articles on Image Processing. Check out the latest volume, Volume 10 issue 1, January-March 2023, at the link below to read the latest research in Image Processing.
https://imanagerpublications.com/journalsfulldetails/24/JournalonImageProcessing

02/03/2023

With the enormous increase in Journals over the recent past and new models of publishing such as open access, and mushrooming of predatory Journals, researchers are at a crossroad over selecting the right Journals for publishing their research. This lecture “Selecting the Right Journal for publishing your Research” presented by Ms. Renisha Winston, Founder and Chairman of i-manager Publications, at Curtin University Dubai as part of Curtin Dubai Research Seminar Series on 27th February 2023 to the students and faculty at their campus, focuses on key factors to look in a Journal such as Relevance to research area, Journal’s reputation and Impact, Editorial quality, Years in Publication etc., and also highlighted on how to identify Predatory, Hijacked and Cloned Journals and pointers to take the right decisions in selecting the Journal. This lecture also narrowed down to Journals to avoid though indexed in Scopus or WoS, and Journals which are at a potentially high risk of removal. This lecture aimed at creating awareness among young researchers and contribute to ethical publishing.

With the enormous increase in Journals over the recent past and new models of publishing such as open access, and mushrooming of predatory Journals, research...

21/02/2023

Join Ms. Renisha Winston, Founder and Chairman of i-manager Publications, at the Curtin Dubai Research Seminar Series on February 27, 2023 at Curtin University Dubai. Her address, "Selecting the Right Journal for Publishing Your Research," will provide valuable insights to help researchers navigate the publishing process.

01/02/2023

We are pleased to release the first Newsletter of 2023..