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.
Principais autores: | Afrin, Anika, Rahman, Md Moshiour, Chowdhury, Ayash Hossain, Eshraq, Mirza, Ukasha, Mehvish Rahman |
---|---|
Outros Autores: | Rahman, Khalilur |
Formato: | Tese |
Idioma: | English |
Publicado em: |
Brac University
2023
|
Assuntos: | |
Acesso em linha: | http://hdl.handle.net/10361/20208 |
Registros relacionados
-
Advancing autonomous navigation: YOLO-based road obstacle detection and segmentation for Bangladeshi environments
por: Mahmud, Ishtiaque, et al.
Publicado em: (2024) -
Real-time garments defects detection at the sewing phase to optimize waste cost using YOLOv7, YOLOv7x, YOLOv7-w6 and Pytorch
por: Uddin, Md. Minhaz, et al.
Publicado em: (2023) -
An ambient assisted living system for Alzheimer’s patients
por: Abedin, Minhajul, et al.
Publicado em: (2023) -
Introducing AI in garment fault detection using YOLOv5 to reduce bottleneck
por: Sanjana, Jasia, et al.
Publicado em: (2024) -
Leveraging robust CNN architectures for real-time object recognition from conveyor belt
por: Moon, Nowrin Tasnim, et al.
Publicado em: (2023)