AI Based Intelligent Baggage Scanner (AIBS) System / (Record no. 611660)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01899nam a22001817a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | NUST |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240923102308.0 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 005.1,ARQ |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Arqam, Muhammad |
| 9 (RLIN) | 125973 |
| 245 ## - TITLE STATEMENT | |
| Title | AI Based Intelligent Baggage Scanner (AIBS) System / |
| Statement of responsibility, etc. | Muhammad Arqam, Muhammad Aashib, Inam Ullah Khan. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | MCS, NUST |
| Name of publisher, distributor, etc. | Rawalpindi |
| Date of publication, distribution, etc. | 2024 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 106 p |
| 505 ## - FORMATTED CONTENTS NOTE | |
| Formatted contents note | This thesis aims at developing the AI-Based Intelligent Baggage Scanner System (AIBS System)<br/>to enhance the detection of contraband items in baggage at airports and other checkpoints.<br/>Leveraging state-of-the-art artificial intelligence models, the AIBS System integrates seamlessly<br/>with existing scanning equipment via an HDMI capture card, offering a cost-effective and easily<br/>deployable solution. The core of AIBS System, is an advanced artificial intelligence algorithm that<br/>has been trained on massive datasets of X-ray images in recognizing prohibited items. When<br/>patterns in the captured images are identified by the system, security personnel receive visual and<br/>sound alerts regarding threats and suspicious objects on baggage, ensuring not only the increase<br/>of the speed of baggage inspections, but also its accuracy. Furthermore, the thesis discusses the<br/>overall system design plan which covers development of the AI mode and the connection of the<br/>proposed AI model with regular baggage scanners will be discussed. The series of comparisons<br/>revealed that the AIBS System consistently outperforms previous approaches in terms of<br/>minimizing both false positives and false negatives. The studies have pointed out major<br/>enhancements in operational effectiveness and security measures in checking points that do lead<br/>to enhanced protective conditions for travel. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | UG BESE |
| 9 (RLIN) | 114271 |
| 651 ## - SUBJECT ADDED ENTRY--GEOGRAPHIC NAME | |
| Geographic name | BESE-26 |
| 9 (RLIN) | 125902 |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Supervisor Dr. Nauman Ali Khan |
| 9 (RLIN) | 112575 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | |
| Koha item type | Project Report |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Permanent Location | Current Location | Shelving location | Date acquired | Total Checkouts | Full call number | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Military College of Signals (MCS) | Military College of Signals (MCS) | General Stacks | 09/23/2024 | 005.1,ARQ | MCSPCS-476 | 09/23/2024 | 09/23/2024 | Project Report |