MARC details
| 000 -LEADER |
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03136ntm a2200373 i 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
| control field |
MY-KuUP |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
| control field |
20251125110822.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS |
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a||||fr|||| 000 0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
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ta |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
| fixed length control field |
231123t20232023my a|||fr|||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
| International Standard Book Number |
THE0009796 (Local) |
| Qualifying information |
Hardback |
| 040 ## - CATALOGING SOURCE |
| Original cataloging agency |
UMP |
| Language of cataloging |
eng |
| Transcribing agency |
UMP |
| Description conventions |
rda |
| 090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
FKOM .I99 2023 r Thesis |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
| Personal name |
Nurul Izzatie Husna Binti Muhamad Fauzi, |
| Relator term |
author. |
| 245 10 - TITLE STATEMENT |
| Title |
Midrange exploration exploitation searching particle swarm optimization with hsv-template matching for crowded environment object tracking / |
| Statement of responsibility, etc. |
Nurul Izzatie Husna Binti Muhamad Fauzi |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
| Place of production, publication, distribution, manufacture |
Kuantan, Pahang : |
| Name of producer, publisher, distributor, manufacturer |
UMP, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2023 |
| 264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
| Date of production, publication, distribution, manufacture, or copyright notice |
©2023 |
| 300 ## - PHYSICAL DESCRIPTION |
| Extent |
vi, 159 pages : |
| Other physical details |
illustrations (some color) ; |
| Dimensions |
30 cm. + |
| Accompanying material |
1 CD-ROM |
| 336 ## - CONTENT TYPE |
| Source |
rdacontent |
| Content type term |
text |
| 336 ## - CONTENT TYPE |
| Source |
rdacontent |
| Content type term |
text |
| 337 ## - MEDIA TYPE |
| Source |
rdamedia |
| Media type term |
unmediated |
| 337 ## - MEDIA TYPE |
| Source |
rdamedia |
| Media type term |
computer |
| 338 ## - CARRIER TYPE |
| Source |
rdacarrier |
| Carrier type term |
volume |
| 338 ## - CARRIER TYPE |
| Source |
rdacarrier |
| Carrier type term |
computer disc |
| 347 ## - DIGITAL FILE CHARACTERISTICS |
| Source |
rda |
| File type |
text file |
| Encoding format |
PDF |
| 500 ## - GENERAL NOTE |
| General note |
Faculty of Computing |
| 502 ## - DISSERTATION NOTE |
| Dissertation note |
Thesis (Doctor of Philosophy) -- Universiti Malaysia Pahang – 2023 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
| Bibliography, etc. note |
Includes bibliographical references |
| 520 3# - SUMMARY, ETC. |
| Summary, etc. |
Particle Swarm Optimization (PSO) has demonstrated its effectiveness in solving the optimization problems. Nevertheless, the PSO algorithm still has the limitation in finding the optimum solution. This is due to the lack of exploration and exploitation of the particle throughout the search space. This problem may also cause the premature convergence, the inability to escape the local optima, and has a lack of self-adaptation in their performance. Therefore, a new variant of PSO called Midrange Exploration Exploitation Searching Particle Swarm Optimization (MEESPSO) was proposed to overcome these drawbacks. In this algorithm, the worst particle will be relocating to a new position to ensure the concept of exploration and exploitation remains in the search space. This is the way to avoid the particles from being trapped in local optima and exploit in a suboptimal solution. The concept of exploration will continue when the particle is relocated to a new position. In addition, to evaluate the performance of MEESPSO, we conducted the experiment on 12 benchmark functions. Meanwhile, for the dynamic environment, the method of MEESPSO with Hue, Saturation, Value (HSV)-template matching was proposed to improve the accuracy and precision of object tracking. Based on 12 benchmarks functions, the result shows a slightly better performance in term of convergence, consistency and error rate compared to another algorithm. The experiment for object tracking was conducted in the PETS09 and MOT20 datasets in a crowded environment with occlusion, similar appearance, and deformation challanges. The result demonstrated that the tracking performance of the proposed method was increased by more than 4.67% and 15% in accuracy and precision compared to other reported works. |
| 610 20 - SUBJECT ADDED ENTRY--CORPORATE NAME |
| Corporate name or jurisdiction name as entry element |
Faculty of Computing |
| General subdivision |
Dissertations |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
| Topical term or geographic name entry element |
Universities and colleges |
| General subdivision |
Dissertations |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
| Topical term or geographic name entry element |
Theses |
| General subdivision |
Dissertations |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Thesis |