Fire and disaster detection with multimodal quadcopter By machine learning
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.
Hlavní autoři: | Afrin, Anika, Rahman, Md Moshiour, Chowdhury, Ayash Hossain, Eshraq, Mirza, Ukasha, Mehvish Rahman |
---|---|
Další autoři: | Rahman, Khalilur |
Médium: | Diplomová práce |
Jazyk: | English |
Vydáno: |
Brac University
2023
|
Témata: | |
On-line přístup: | http://hdl.handle.net/10361/20208 |
Podobné jednotky
-
Advancing autonomous navigation: YOLO-based road obstacle detection and segmentation for Bangladeshi environments
Autor: Mahmud, Ishtiaque, a další
Vydáno: (2024) -
Real-time garments defects detection at the sewing phase to optimize waste cost using YOLOv7, YOLOv7x, YOLOv7-w6 and Pytorch
Autor: Uddin, Md. Minhaz, a další
Vydáno: (2023) -
An ambient assisted living system for Alzheimer’s patients
Autor: Abedin, Minhajul, a další
Vydáno: (2023) -
Introducing AI in garment fault detection using YOLOv5 to reduce bottleneck
Autor: Sanjana, Jasia, a další
Vydáno: (2024) -
Leveraging robust CNN architectures for real-time object recognition from conveyor belt
Autor: Moon, Nowrin Tasnim, a další
Vydáno: (2023)