Garuda - Garba Rujukan Digital

p-Index From 2021 - 2026

0.61

P-Index

This Author published in this journals

All Journal International Journal of Informatics and Communication Technology (IJ-ICT) International Journal of Advances in Applied Sciences

Kamoli Akinwale Amusa

Federal University of Agriculture

Author-ID : 5438565

Computer Science & IT Earth & Planetary Sciences Environmental Science Materials Science & Nanotechnology Mathematics Physics

Published : 3 Documents Claim Missing Document

Claim Missing Document

Articles

Digital terrestrial television in Nigeria: A technical review of path loss modeling and optimization techniques Abolaji Okikiade Ilori; Kamoli Akinwale Amusa; Tolulope Christianah Erinosho
International Journal of Advances in Applied Sciences Vol 11, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

The switch from analog to digital terrestrial broadcasting (DTTV) has resulted in a substantial shift in the contemporary television broadcasting environment, introducing a new means of transmitting content, as well as a new and upgraded process that will improve consumer satisfaction by ensuring greater reception. Despite the deadline, only a small percentage of terrestrial television stations in Nigeria have been digitalized. This work takes a critical review of various aspects of DTTV implementation, ranging from evolution to path loss estimation, prospects and challenges associated with the switch-over on the very high frequency (VHF) communication links as well as various optimization techniques that are adopted for DTTV in Nigeria and sub-Sahara Africa. Findings show that the prospects are bright and numerous benefits are accruable if the government of Nigeria can solve the problems facing its full migration. Furthermore, investigations into the path-loss of DTTV in the ultra-high frequency (UHF) communication links have enjoyed scanty attention, therefore, careful examination and suitable path-loss model development in this frequency regime for television (TV) services across various ecological and vegetation zones should be considered as it will aid the full deployment of DTTV in Nigeria.

Tri-modal technique for medical images enhancement Kamoli Akinwale Amusa; Olumayowa Ayodeji Idowu; Isaiah Adediji Adejumobi; Gboyega Augustine Adebayo
International Journal of Advances in Applied Sciences Vol 11, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Owing to methods of acquisition, medical images often require enhancement for them to serve the intended purpose of computer-aided diagnosis. Most medical image enhancement techniques are application specific, leading to the introduction of different enhancement methods for different medical images. In addition, the execution time of most of the previous enhancement methods is longer than necessary. Hence, there is a need for a method that produces fast and satisfactory results when deployed for the enhancement of several medical images. This paper proposes a tri-modal technique, involving a hybrid combination of unsharp masking, logarithmic transformation, and histogram equalization approaches, for medical image enhancement. Three classes of medical images: X-ray, magnetic resonance, and computer tomographic images are used for the evaluations of the proposed tri-modal method, where absolute mean brightness error, peak signal-to-noise ratio, and entropy are utilized as performance metrics. Both qualitative and quantitative evaluations reveal that the proposed tri-modal method performed better than the four previous methods in the literature for the three classes of medical images used in the evaluation. Also, the execution time of the tri-modal technique compares well with those of mono-mode methods. Thus, the tri-modal technique produces better enhanced medical images from different medical image inputs.

Development of a PC-based sign language translator Kamoli Akinwale Amusa; Ayorinde Joseph Olanipekun; Tolulope Christiana Erinosho; Abiodun Akeem Salaam; Sodiq Segun Razaq
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 12, No 1: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v12i1.pp23-31

While a hearing-impaired individual depends on sign language and gestures, non-hearing-impaired person uses verbal language. Thus, there is need for means of arbitration to forestall situation when a non-hearing-impaired individual who does not understand the sign language wants to communicate with a hearing-impaired person. This paper is concerned with the development of a PC-based sign language translator to facilitate effective communication between hearing-impaired and non-hearing-impaired persons. Database of hand gestures in American sign language (ASL) is created using Python scripts. TensorFlow (TF) is used in the creation of a pipeline configuration model for machine learning of annotated images of gestures in the database with the real time gestures. The implementation is done in Python software environment and it runs on a PC equipped with a web camera to capture real time gestures for comparison and interpretations. The developed sign language translator is able to translate ASL/gestures to written texts along with corresponding audio renderings at an average duration of about one second. In addition, the translator is able to match real time gestures with the equivalent gesture images stored in the database even at 44% similarity.

Co-Authors Abiodun Akeem Salaam Abolaji Okikiade Ilori Ayorinde Joseph Olanipekun Gboyega Augustine Adebayo Isaiah Adediji Adejumobi Olumayowa Ayodeji Idowu Sodiq Segun Razaq Tolulope Christiana Erinosho Tolulope Christianah Erinosho

Title

Found 3 Documents
Search

Abstract

Abstract

Abstract

Title Search

Found 3 Documents Search

Abstract

Abstract

Abstract

Title

Found 3 Documents
Search