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.
Hoofdauteurs: | Afrin, Anika, Rahman, Md Moshiour, Chowdhury, Ayash Hossain, Eshraq, Mirza, Ukasha, Mehvish Rahman |
---|---|
Andere auteurs: | Rahman, Khalilur |
Formaat: | Thesis |
Taal: | English |
Gepubliceerd in: |
Brac University
2023
|
Onderwerpen: | |
Online toegang: | http://hdl.handle.net/10361/20208 |
Gelijkaardige items
-
Advancing autonomous navigation: YOLO-based road obstacle detection and segmentation for Bangladeshi environments
door: Mahmud, Ishtiaque, et al.
Gepubliceerd in: (2024) -
Real-time garments defects detection at the sewing phase to optimize waste cost using YOLOv7, YOLOv7x, YOLOv7-w6 and Pytorch
door: Uddin, Md. Minhaz, et al.
Gepubliceerd in: (2023) -
An ambient assisted living system for Alzheimer’s patients
door: Abedin, Minhajul, et al.
Gepubliceerd in: (2023) -
Introducing AI in garment fault detection using YOLOv5 to reduce bottleneck
door: Sanjana, Jasia, et al.
Gepubliceerd in: (2024) -
Leveraging robust CNN architectures for real-time object recognition from conveyor belt
door: Moon, Nowrin Tasnim, et al.
Gepubliceerd in: (2023)