paper-with-me

Papers

Exploring the Feasibility of Affordable Sonar Technology: Object Detection in Underwater Environments Using the Ping 360

2024-11-07 · Md Junayed Hasan, Somasundar Kannan, Ali Rohan, Mohd Asif Shah

This study explores the potential of the Ping 360 sonar device, primarily used for navigation, in detecting complex underwater obstacles. The key motivation behind this research is the device's affordability and open-source nature, offering a cost-effective alternative to more expensive imaging sonar systems. The investigation focuses on understanding the behaviour of the Ping 360 in controlled environments and assessing its suitability for object detection, particularly in scenarios where human operators are unavailable for inspecting offshore structures in shallow waters. Through a series of carefully designed experiments, we examined the effects of surface reflections and object shadows in shallow underwater environments. Additionally, we developed a manually annotated sonar image dataset to train a U-Net segmentation model. Our findings indicate that while the Ping 360 sonar demonstrates potential in simpler settings, its performance is limited in more cluttered or reflective environments unless extensive data pre-processing and annotation are applied. To our knowledge, this is the first study to evaluate the Ping 360's capabilities for complex object detection. By investigating the feasibility of low-cost sonar devices, this research provides valuable insights into their limitations and potential for future AI-based interpretation, marking a unique contribution to the field.

📄 PDF Abstract BibTeX arXiv:2411.05863

Code (1)

junayed/sonar-scan-dataset-with-ping-360 공식 구현

Tasks

object-detectionObject Detection

Methods 이 논문이 사용한 방법론

Concatenated Skip Connection A Concatenated Skip Connection is a type of skip connection that seeks to reuse features by concatenating them to new layers, allowing more information to be retained from…
Max Pooling Max Pooling is a pooling operation that calculates the maximum value for patches of a feature map, and uses it to create a downsampled (pooled) feature map. It is usually…
Convolution A convolution is a type of matrix operation, consisting of a kernel, a small matrix of weights, that slides over input data performing element-wise multiplication with the…
ReLU How Do I Communicate to Expedia? How Do I Communicate to Expedia? – Call ☎️ +1-(888) 829 (0881) or +1-805-330-4056 or +1-805-330-4056 for Live Support & Special Travel…
U-Net 설명 없음

Similar Papers 제목 키워드 기반

RSOD: Reliability-Guided Sonar Image Object Detection with Extremely Limited Labels

2026-01-19 · Chengzhou Li, Ping Guo, Guanchen Meng, Qi Jia 외 arxiv

Object detection in sonar images is a key technology in underwater detection systems. Compared to natural images, sonar images contain fewer texture details and are more susceptible to noise, making it difficult for non-…

Object Detection

Underwater object detection in sonar imagery with detection transformer and Zero-shot neural architecture search

2025-05-10 · Xiaotong Gu, Shengyu Tang, Yiming Cao, Changdong Yu

Underwater object detection using sonar imagery has become a critical and rapidly evolving research domain within marine technology. However, sonar images are characterized by lower resolution and sparser features compar…

Neural Architecture SearchObjectobject-detectionObject Detection

Counting Fish with Temporal Representations of Sonar Video

2025-02-07 · Kai Van Brunt, Justin Kay, Timm Haucke, Pietro Perona 외

Accurate estimates of salmon escapement - the number of fish migrating upstream to spawn - are key data for conservation and fishery management. Existing methods for salmon counting using high-resolution imaging sonar ha…

object-detectionObject Detection

RSFusionDet: Underwater RGB-Sonar Multimodal Object Detection

2026-08-26 · Zhuoyan Liu, Yihan Wang, Bo Wang, Bing Wang 외 arxiv

Underwater unimodal object detection faces many challenges in sensor imaging, such as optical images limited by underwater noise and visible distance, and sonar images limited by less object structural information. While…

Object Detection

Advances in Self-Supervised Learning for Synthetic Aperture Sonar Data Processing, Classification, and Pattern Recognition

2023-08-12 · Brandon Sheffield, Frank E. Bobe III, Bradley Marchand, Matthew S. Emigh

Synthetic Aperture Sonar (SAS) imaging has become a crucial technology for underwater exploration because of its unique ability to maintain resolution at increasing ranges, a characteristic absent in conventional sonar t…

object-detectionObject DetectionSelf-Supervised Learning