Volume 23 (2023)
Volume 22 (2022)
Volume 21 (2021)
Volume 20 (2020)
Volume 19 (2019)
Volume 18 (2018)
Volume 17 (2017)
Volume 16 (2016)
Volume 15 (2015)
Volume 14 (2014)
Volume 13 (2013)
Volume 12 (2012)
Volume 11 (2011)
Volume 10 (2010)
Volume 9 (2009)
Volume 8 (2008)
Volume 7 (2007)
Volume 6 (2006)
Volume 5 (2005)
Volume 4 (2004)
Automatic Translation From Iraqi Sign Language to Arabic Text or Speech Using CNN

Raja’a M. Mohammed; Suhad M. Kadhem

Volume 23, Issue 2 , June 2023, , Page 112-124


  Sign language (SL) is Non-verbal communication and a way for thedeaf and mute to communicate without words. A deaf and mute person's hands,face, and body shows what they want to say. Since the number of deaf and dumbpeople is increasing, there must be other ways to learn sign language orcommunicate with ...  Read More ...

Object Detection Using Deep Learning Methods: A Review

Asmaa Hasan Alrubaie; Maisa'a Abid Ali Khodher; Ahmed Talib Abdulameer

Volume 23, Issue 2 , June 2023, , Page 136-152


  Target detection, one of the key functions of computer vision, has grown in importance as a study area over the past two decades and is currently often employed. In a certain video, it seeks to rapidly and precisely detect and locate a huge amount of the objects according to redetermined categories. ...  Read More ...

A survey on Deep Learning Face Synthesis and Animation Techniques Used in Deepfake

Suha Mohammed Saleh; Abdulamir A. Karim

Volume 23, Issue 2 , June 2023, , Page 153-159


  From big data analytics to computer vision and human-level control, deep learning has been effectively applied to a wide range of complicated challenges. However, these same deep learning advancements have also been used to develop malicious software that threatens individuals' personal data, democratic ...  Read More ...

Abnormal Behavior Detection in Video Surveillance Using Inception-v3 Transfer Learning Approaches

Sabah Abdulazeez Jebur; Khalid A. Hussein; Haider Kadhim Hoomod

Volume 23, Issue 2 , June 2023, , Page 210-221


  The use of video surveillance systems has increased due to security concerns and their relatively low cost. Researchers are working to create intelligent Closed Circuit Television (CCTV) cameras that can automatically analyze behavior in real-time to detect anomalous behaviors and prevent dangerous accidents. ...  Read More ...

Architecture of Deep Learning and Its Applications

Afrah Salman Dawood; Zena Mohammed Faris

Volume 23, Issue 1 , March 2023, , Page 35-56


  Recently, Deep Learning (DL) has accomplished enormous prosperity in various areas, like natural language processing (NLP), image processing, different medical issues and computer vision. Both Machine Learning (ML) and DL as compared to traditional methods, can learn and make better and enhanced use ...  Read More ...

Deep Learning Based on Attention in Semantic Segmentation: An Introductory Survey

Muna Khalaf; Ban N. Dhannoon

Volume 23, Issue 1 , March 2023, , Page 104-114


  Semantic segmentation refers to labeling each pixel in the scene to its belonging object. It is a critical task for many computer vision applications that requires scene understanding because It attempts to mimic human perceptual grouping. Despite the unremitting efforts in this field, it is still a ...  Read More ...

Unmasking Deepfakes Based on Deep Learning and Noise Residuals

Wildan J. Jameel; Suhad M. Kadhem; Ayad R. Abbas

Volume 22, Issue 3 , September 2022, , Page 111-117


  The main reason for the emergence of a deepfake (deep learning and fake) term is the evolution in artificial intelligence techniques, especially deep learning. Deep learning algorithms, which auto-solve problems when giving large sets of data, are used to swap faces in digital media to create fake media ...  Read More ...

Convolutional Recurrent Neural Networks for Text Lecture Summarization

Muna Ghazi; Matheel Abdulmunim

Volume 22, Issue 2 , June 2022, , Page 27-39


  Text summarization can be utilized for variety type of purposes; one of them for summary lecture file. A long document expended long time and large capacity. Since it may contain duplicated information, more over, irrelevant details that take long period to access relevant information. Summarization ...  Read More ...

Detection And Count of Human Bodies In a Crowd Scene Based on Enhancement Features By Using The YOLO v5 Algorithm

Mohammed Abduljabbar Ali; Abir Jaafar Hussain; Ahmed T. Sadiq

Volume 22, Issue 2 , June 2022, , Page 125-134


  Crowd detection has various applications nowadays. However, detecting humans in crowded circumstances is difficult because the features of different objects conflict, making cross-state detection impossible. Detectors in the overlapping zone may therefore overreact. The proposal uses the YOLO v5 (You ...  Read More ...

Detection Covid-19 Based on Chest X-ray Images Using Convolution Neural Networks

sufyan zaben; Akbas Ezaldeen Ali

Volume 22, Issue 1 , March 2022, , Page 34-42


  Covid-19 is a deadly virus that has spread worldwide, causing millions of deaths. Chest X-ray is one of the most common methods of diagnosing the infection of Covid - 19. Therefore, this paper has presented an efficient method to detect Covid-19 through X-rays of the chest area through a Neural convolution ...  Read More ...

Indoor Localization Using Deep-Learning and Smartphone

Zainab Mohammed Resan; Muayad Sadik Croock

Volume 19, Issue 3 , July 2019, , Page 40-49


  Robust and accurate indoor localization has been the goal of several researchefforts over the past decade. In the building where the GPS is not available, this projectcan be utilized. Indoor localization based on image matching techniques related to deeplearning was achieved in a hard environment. So, ...  Read More ...