ijsab.com logo

Impact of Deep Learning on Transfer Learning : A Review Mohammed Jameel Barwary & Adnan Mohsin Abdulazeez

Impact of Deep Learning on Transfer Learning : A Review

Author (s)

Mohammed Jameel Barwary & Adnan Mohsin Abdulazeez

 

Abstract

­

Transfer learning and deep learning approaches have been utilised in several real-world applications and hierarchical systems for pattern recognition and classification tasks. However, in few of the real-world machine learning situations, this presumption does not sustain since there are instances where training data is costly or tough to gather and there is continually a necessity to produce high-performance learners competent with more easily attained data from diverse fields. The objective of this review is to determine more abstract qualities at the greater levels of the representation, by utilising deep learning to detach the variables in the outcomes, formally outline transfer learning, provide information on present solutions, and appraise applications employed in diverse facets of transfer learning and deep learning. This can be attained by rigorous literature exploration and discussion on all presently accessible techniques and prospective research studies on transfer learning solutions of independent as well as big data scale. The conclusions of this study could be an effectual platform directed at prospective directions for devising new deep learning patterns for different applications and dealing with the challenges concerned.

 Keywords: Machine Learning, Transfer Learning, Deep Learning, classifications, Supervised Learning techniques.

 

Download PDF

Title: Impact of Deep Learning on Transfer Learning : A Review
Author: Mohammed Jameel Barwary & Adnan Mohsin Abdulazeez
Journal Name: International Journal of Science and Business
Website: ijsab.com
ISSN: ISSN 2520-4750 (Online), ISSN 2521-3040 (Print)
DOI: https://doi.org/10.5281/zenodo.4559668
Media: Online
Volume: 5
Issue: 3
Acceptance Date: 6/02/2021
Date of Publication: 24/02/2021
PDF URL: https://ijsab.com/wp-content/uploads/698.pdf
Free download: Available
Page: 204-216
First Page: 204
Last Page: 216
Paper Type: Literature Review
Current Status: Published

 

Cite This Article:

Barwary, M. J. & Abdulazeez, A. M. (2021). Impact of Deep Learning on Transfer Learning : A Review. International Journal of Science and Business, 5(3), 204-216. doi: https://doi.org/ 10.5281/zenodo.4559668

Retrieved from https://ijsab.com/wp-content/uploads/698.pdf

 

About Author (s)

Mohammed Jameel Barwary (corresponding author), Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq. Email: mohammed.jameel@uod.ac

Professor Adnan Mohsin Abdulazeez, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq.

 

 Download PDF

DOI: https://doi.org/10.5281/zenodo.4559668

ijsab.com logo

Deep Learning Convolutional Neural Network for Speech Recognition: A Review Kazheen Ismael Taher & Adnan Mohsin Abdulazeez

Deep Learning Convolutional Neural Network for Speech Recognition: A Review

Author (s)

Kazheen Ismael Taher & Adnan Mohsin Abdulazeez

Abstract

­In the last few decades, there has been considerable amount of research on the use of Machine Learning (ML) for speech recognition based on Convolutional Neural Network (CNN). These studies are generally focused on using CNN for applications related to speech recognition. Additionally, various works are discussed that are based on deep learning since its emergence in the speech recognition applications. Comparing to other approaches, the approaches based on deep learning are showing rather interesting outcomes in several applications including speech recognition, and therefore, it attracts a lot of researches and studies. In this paper, a review is presented on the developments that occurred in this field while also discussing the current researches that are being based on the topic currently.

 Keywords: Machine Learning, Speech Recognition, Convolutional Neural Networks, Deep Learning, Word Error Rate (WER).

Download PDF

Title: Deep Learning Convolutional Neural Network for Speech Recognition: A Review
Author: Kazheen Ismael Taher & Adnan Mohsin Abdulazeez
Journal Name: International Journal of Science and Business
Website: ijsab.com
ISSN: ISSN 2520-4750 (Online), ISSN 2521-3040 (Print)
DOI: https://doi.org/10.5281/zenodo.4475361
Media: Online
Volume: 5
Issue: 3
Acceptance Date: 24/01/2021
Date of Publication: 28/01/2021
PDF URL: https://ijsab.com/wp-content/uploads/681.pdf
Free download: Available
Page: 1-14
First Page: 1
Last Page: 14
Paper Type: Literature Review
Current Status: Published

 

Cite This Article:

Kazheen Ismael Taher & Adnan Mohsin Abdulazeez (2021). Deep Learning Convolutional Neural Network for Speech Recognition: A Review. International Journal of Science and Business, 5(3), 1-14. doi: https://doi.org/10.5281/zenodo.4475361

Retrieved from https://ijsab.com/wp-content/uploads/681.pdf

 

About Author (s)

Kazheen Ismael Taher (corresponding author), Information Technology Department, Akre Technical College of Informatics, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq. E-mail: kajeen.ismael@gmail.com

Professor Adnan Mohsin Abdulazeez, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq. E-mail: adnan.mohsin@dpu.edu.krd

 

 Download PDF

DOI: https://doi.org/10.5281/zenodo.4475361

ijsab.com logo

Deep Learning Convolutional Neural Network for Face Recognition: A Review Rondik J. Hassan & Adnan Mohsin Abdulazeez

Deep Learning Convolutional Neural Network for Face Recognition:

A Review

Author (s)

Rondik J. Hassan & Adnan Mohsin Abdulazeez

Abstract

­Face recognition is increasingly being used for solving various social-problems such as personal protection and authentication. As with other widely used biometric applications, facial recognition is a biometric instrument such as iris recognition, vein pattern recognition, and fingerprint recognition. Facial recognition identifies a person based on certain aspects of his physiology. Deep Learning (DL) is a branch of machine learning (ML) that can be used in image processing and pattern recognition to solve multiple problems, one of the applications is face recognition. With the advancement of deep learning, Convolution Neural Network (CNN) based facial recognition technology has been the dominant approach adopted in the field of face recognition. The purpose of this paper is to provide a review of face recognition approaches. Furthermore, the details of each paper, such as used datasets, algorithms, architecture, and achieved results are summarized and analyzed comprehensively.

 Keywords: Face Recognition, Machine Learning, Deep Learning, Convolution Neural Network, Feature Extraction, Feature Matching.

Download PDF

Title: Deep Learning Convolutional Neural Network for Face Recognition: A Review
Author: Rondik J. Hassan & Adnan Mohsin Abdulazeez
Journal Name: International Journal of Science and Business
Website: ijsab.com
ISSN: ISSN 2520-4750 (Online), ISSN 2521-3040 (Print)
DOI: https://doi.org/10.5281/zenodo.4471013
Media: Online
Volume: 5
Issue: 2
Acceptance Date: 24/01/2021
Date of Publication: 27/01/2021
PDF URL: https://ijsab.com/wp-content/uploads/675.pdf
Free download: Available
Page: 114-127
First Page: 114
Last Page: 127
Paper Type: Literature Review
Current Status: Published

 

Cite This Article:

Rondik J. Hassan & Adnan Mohsin Abdulazeez (2021). Deep Learning Convolutional Neural Network for Face Recognition: A Review, International Journal of Science and Business, 5(2), 114-127. doi: https://doi.org/ 10.5281/zenodo.4471013

Retrieved from https://ijsab.com/wp-content/uploads/675.pdf

 

About Author (s)

Rondik J.Hassan (corresponding author), Information Technology Department, Akre Technical College of Informatics, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq.  E-mail: rondik.jamaluddin@gmail.com

Professor Adnan Mohsin Abdulazeez, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq. E-mail: adnan.mohsin@dpu.edu.krd

 

 Download PDF

DOI: https://doi.org/10.5281/zenodo.4471013

ijsab.com logo

Human Diseases Detection Based On Machine Learning Algorithms: A Review Nareen O. M. Salim & Adnan Mohsin Abdulazeez

Human Diseases Detection Based On Machine Learning Algorithms: A Review

Author (s)

Nareen O. M. Salim & Adnan Mohsin Abdulazeez

Abstract

­One of the most significant subjects of society is human healthcare. It is looking for the best one and robust disease diagnosis to get the care they need as soon as possible. Other fields, such as statistics and computer science, are needed for the health aspect of searching since this recognition is often complicated. The task of following new approaches is challenging these disciplines, moving beyond the conventional ones. The actual number of new techniques makes it possible to provide a broad overview that avoids particular aspects. To this end, we suggest a systematic analysis of human diseases related to machine learning. This research concentrates on existing techniques related to machine learning growth applied to the diagnosis of human illnesses in the medical field to discover exciting trends, make unimportant predictions, and help decision-making. This paper analyzes unique machine learning algorithms used for healthcare applications to create adequate decision support. This paper intends to reduce the research gap in creating a realistic decision support system for medical applications.

 Keywords: Human disease, Healthcare, Machine learning, Deep learning, Convolutional Neural Networks.

Download PDF

Title: Human Diseases Detection Based On Machine Learning Algorithms: A Review
Author: Nareen O. M. Salim & Adnan Mohsin Abdulazeez
Journal Name: International Journal of Science and Business
Website: ijsab.com
ISSN: ISSN 2520-4750 (Online), ISSN 2521-3040 (Print)
DOI: https://doi.org/10.5281/zenodo.4467510
Media: Online
Volume: 5
Issue: 2
Acceptance Date: 19/01/2021
Date of Publication: 25/01/2021
PDF URL: https://ijsab.com/wp-content/uploads/674.pdf
Free download: Available
Page: 102-113
First Page: 102
Last Page: 113
Paper Type: Literature Review
Current Status: Published

 

Cite This Article:

Nareen O. M. Salim & Adnan Mohsin Abdulazeez (2021). Human Diseases Detection Based On Machine Learning Algorithms: A Review. International Journal of Science and Business, 5(2), 102-113. doi: https://doi.org/10.5281/zenodo.4462858

Retrieved from https://ijsab.com/wp-content/uploads/674.pdf

 

About Author (s)

Nareen O. M. Salim, Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq.

Adnan Mohsin Abdulazeez (corresponding author), Duhok Polytechnic University, Duhok, Kurdistan Region, Iraq. Email: nareen.mohameed@dpu.edu.krd

 

 Download PDF

DOI: https://doi.org/10.5281/zenodo.4467510

ijsab.com logo

Deep Learning Models Based on Image Classification: A Review Kavi B. Obaid, Subhi R. M. Zeebaree & Omar M. Ahmed

Deep Learning Models Based on Image Classification: A Review

Author (s)

Kavi B. Obaid, Subhi R. M. Zeebaree & Omar M. Ahmed

Abstract

With the development of the big data age, deep learning developed to become having a more complex network structure and more powerful feature learning and feature expression abilities than traditional machine learning methods. The model trained by the deep learning algorithm has made remarkable achievements in many large-scale identification tasks in the field of computer vision since its introduction. This paper first introduces the deep learning, and then the latest model that has been used for image classification by deep learning are reviewed.  Finally, all used deep learning models in the literature have been compared to each other in terms of accuracy for the two most challenging datasets CIFAR-10 and CIFAR-100.

 Keywords: Deep Learning, Image Classification, Machine Learning, Models.

Download PDF

Title: Deep Learning Models Based on Image Classification: A Review
Author: Kavi B. Obaid, Subhi R. M. Zeebaree & Omar M. Ahmed
Journal Name: International Journal of Science and Business
Website: ijsab.com
ISSN: ISSN 2520-4750 (Online), ISSN 2521-3040 (Print)
DOI: https://doi.org/10.5281/zenodo.4108433
Media: Online
Volume: 4
Issue: 11
Acceptance Date: 13/10/2020
Date of Publication: 20/10/2020
PDF URL: https://ijsab.com/wp-content/uploads/612.pdf
Free download: Available
Page: 75-81
First Page: 75
Last Page: 81
Paper Type: Research article
Current Status: Published

 

Cite This Article:

Kavi B. Obaid, Subhi R. M. Zeebaree & Omar M. Ahmed (2020). Deep Learning Models Based on Image Classification: A Review. International Journal of Science and Business, 4(11), 75-81. doi: https://doi.org/10.5281/zenodo.4108433

Retrieved from https://ijsab.com/wp-content/uploads/612.pdf

 

About Author (s)

Kavi B. Obaid, Computer Science Department, College of Science, University of Zakho, Iraq (e-mail: kavi.obaid@uoz.edu.krd).

Subhi R. M. Zeebaree, Duhok Polytechnic University, Iraq (e-mail: subhi.rafeeq@dpu.edu.krd).

Omar M. Ahmed, (Corresponding author),Information Technology Department, Zakho Technical Institute, Duhok Polytechnic University, Iraq (e-mail: omar.alzakholi@uoz.edu.krd).

 

 

Download PDF

DOI: https://doi.org/10.5281/zenodo.4108433