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.
Κύριοι συγγραφείς: | Afrin, Anika, Rahman, Md Moshiour, Chowdhury, Ayash Hossain, Eshraq, Mirza, Ukasha, Mehvish Rahman |
---|---|
Άλλοι συγγραφείς: | Rahman, Khalilur |
Μορφή: | Thesis |
Γλώσσα: | English |
Έκδοση: |
Brac University
2023
|
Θέματα: | |
Διαθέσιμο Online: | http://hdl.handle.net/10361/20208 |
Παρόμοια τεκμήρια
-
Advancing autonomous navigation: YOLO-based road obstacle detection and segmentation for Bangladeshi environments
ανά: Mahmud, Ishtiaque, κ.ά.
Έκδοση: (2024) -
Real-time garments defects detection at the sewing phase to optimize waste cost using YOLOv7, YOLOv7x, YOLOv7-w6 and Pytorch
ανά: Uddin, Md. Minhaz, κ.ά.
Έκδοση: (2023) -
An ambient assisted living system for Alzheimer’s patients
ανά: Abedin, Minhajul, κ.ά.
Έκδοση: (2023) -
Introducing AI in garment fault detection using YOLOv5 to reduce bottleneck
ανά: Sanjana, Jasia, κ.ά.
Έκδοση: (2024) -
Leveraging robust CNN architectures for real-time object recognition from conveyor belt
ανά: Moon, Nowrin Tasnim, κ.ά.
Έκδοση: (2023)