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)
Computer
A New Perspective for Mining COCO Dataset

Suha Dh. Athab; Kesra Nermend; Abdulamir Abdullah Karim

Volume 23, Issue 3 , September 2023, , Page 80-89

https://doi.org/https://doi.org/10.33103/uot.ijccce.23.3.7

Abstract
  Microsoft Common Objects in Context (COCO) is a huge image dataset that has over 300 k images belonging to more than ninety-one classes. COCO has valuable information in the field of detection, segmentation, classification, and tagging; but the COCO dataset suffers from being unorganized, and classes ...  Read More ...

Computer
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

https://doi.org/https://doi.org/10.33103/uot.ijccce.23.2.11

Abstract
  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 ...

Dual Architecture Deep Learning Based Object Detection System for Autonomous Driving

Mahmoud M. Mahmoud; Ahmed R. Nasser

Volume 21, Issue 2 , June 2021, , Page 36-43

Abstract
  Object detection of autonomous vehicles presents a big challenge forresearchers due to the requirements of accuracy and precision in real-time.This work presents a deep learning approach based on a dual architecturedesign of the network. A highly accurate multi-class network of convolutionalneural networks ...  Read More ...