Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
Enhanced YOLO11 for lightweight and accurate drone-based maritime search and rescue object detection
by
Zhao, Jiawen
, Liu, Jiren
, Song, Rui
, Zhao, Beigeng
, Zhang, Xia
, Yu, Lizhi
in
Ablation
/ Accuracy
/ Algorithms
/ Architecture
/ Biology and Life Sciences
/ Computer and Information Sciences
/ Computer vision
/ Configurations
/ Datasets
/ Design
/ Drone aircraft
/ Drones
/ Efficiency
/ Engineering and Technology
/ Evacuations & rescues
/ Humans
/ Image Processing, Computer-Assisted - methods
/ Machine vision
/ Medicine and Health Sciences
/ Object recognition
/ Performance evaluation
/ Rescue operations
/ Rescue Work - methods
/ Research and Analysis Methods
/ Science Policy
/ Search and rescue
/ Search and rescue operations
/ Searching
/ Sensors
/ Ships
/ Technology application
/ Telematics
2025
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Enhanced YOLO11 for lightweight and accurate drone-based maritime search and rescue object detection
by
Zhao, Jiawen
, Liu, Jiren
, Song, Rui
, Zhao, Beigeng
, Zhang, Xia
, Yu, Lizhi
in
Ablation
/ Accuracy
/ Algorithms
/ Architecture
/ Biology and Life Sciences
/ Computer and Information Sciences
/ Computer vision
/ Configurations
/ Datasets
/ Design
/ Drone aircraft
/ Drones
/ Efficiency
/ Engineering and Technology
/ Evacuations & rescues
/ Humans
/ Image Processing, Computer-Assisted - methods
/ Machine vision
/ Medicine and Health Sciences
/ Object recognition
/ Performance evaluation
/ Rescue operations
/ Rescue Work - methods
/ Research and Analysis Methods
/ Science Policy
/ Search and rescue
/ Search and rescue operations
/ Searching
/ Sensors
/ Ships
/ Technology application
/ Telematics
2025
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Enhanced YOLO11 for lightweight and accurate drone-based maritime search and rescue object detection
by
Zhao, Jiawen
, Liu, Jiren
, Song, Rui
, Zhao, Beigeng
, Zhang, Xia
, Yu, Lizhi
in
Ablation
/ Accuracy
/ Algorithms
/ Architecture
/ Biology and Life Sciences
/ Computer and Information Sciences
/ Computer vision
/ Configurations
/ Datasets
/ Design
/ Drone aircraft
/ Drones
/ Efficiency
/ Engineering and Technology
/ Evacuations & rescues
/ Humans
/ Image Processing, Computer-Assisted - methods
/ Machine vision
/ Medicine and Health Sciences
/ Object recognition
/ Performance evaluation
/ Rescue operations
/ Rescue Work - methods
/ Research and Analysis Methods
/ Science Policy
/ Search and rescue
/ Search and rescue operations
/ Searching
/ Sensors
/ Ships
/ Technology application
/ Telematics
2025
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Enhanced YOLO11 for lightweight and accurate drone-based maritime search and rescue object detection
Journal Article
Enhanced YOLO11 for lightweight and accurate drone-based maritime search and rescue object detection
2025
Request Book From Autostore
and Choose the Collection Method
Overview
Accurately and rapidly detecting objects and their locations in drone-captured images from maritime search and rescue scenarios provides valuable information for rescue operations. The YOLO series, known for its balance between lightweight architecture and high accuracy, has become a popular method among researchers in this field. Recent advancements in the newly released YOLO11 model have demonstrated significant progress in general object detection tasks across everyday scenarios. However, its application to the specific task of drone-based maritime search and rescue still leaves substantial room for improvement. To address this gap, we propose targeted optimizations to enhance YOLO11’s performance in this domain. These include integrating a Space-to-Depth module into the Backbone, incorporating a content-aware upsampling algorithm in the Neck, and adding an extra detection head to better exploit shallow image features. These modifications significantly improve the model’s ability to detect small, overlapping, and rarely occurring objects, which are common challenges in maritime search and rescue tasks. Experimental evaluations conducted on the large-scale SeaDronesSee dataset demonstrate that the proposed optimized YOLO11 outperforms YOLOv8, YOLO11, and MambaYOLO across all scales. Moreover, under lightweight configurations, the model achieves substantial performance gains over YoloOW, a method renowned for its accuracy but depends on heavyweight configurations. In the lightweight complexity range, the proposed model achieves a relative accuracy improvement of 20.85% to 43.70% compared to these state-of-the-art methods. The code supporting this research is available at https://github.com/bgno1/sds_yolo11 .
Publisher
Public Library of Science,Public Library of Science (PLoS)
MBRLCatalogueRelatedBooks
Related Items
Related Items
We currently cannot retrieve any items related to this title. Kindly check back at a later time.
This website uses cookies to ensure you get the best experience on our website.