N., Janaki (2025) Buried Landmine Detection Using Deep Convolutional Neural Networks. In: Proceedings of International Conference on Paradigms of Communication, Computing and Data Analytics PCCDA 2025, Volume 1.
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Abstract
The global rise in terrorism increases on a daily basis, despite the advancements in government measures for combating terrorists. This has posed a serious threat to the
government and civilians. The development of more security systems is required to curb this menace. The use of weapons by terrorists has a significant impact on the public, psychological effects, and economic costs of society. Thousands of people die annually as a result of terrorist’s violence. It is affirmed that children that are exposed to high levels of terrorism in their communities usually face a high level of psychological trauma [1]. Children that witness terrorist activities or those that become victims can experience negative psychological effects for a very long time. There are two different types of weapons: the primary weapon and the secondary weapon. Studies show that handheld guns and knives are the primary weapons mostly
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Electrical and Electronics Engineering > Power Electronics |
| Domains: | Electrical and Electronics Engineering |
| Depositing User: | Mr Vivek R |
| Date Deposited: | 12 Dec 2025 08:06 |
| Last Modified: | 16 Dec 2025 09:00 |
| URI: | https://ir.vistas.ac.in/id/eprint/11416 |


