Results 61 to 70 of about 20,770 (204)

An End-to-End Underwater Acoustic Target Recognition Model Based on One-Dimensional Convolution and Transformer

Journal of Marine Science and Engineering
Underwater acoustic target recognition (UATR) is crucial for defense and ocean environment monitoring. Although traditional methods and deep learning approaches based on time–frequency domain features have achieved high recognition rates in certain tasks,
Kang Yang, Biao Wang, Zide Fang, Banggui Cai   +3 more
doaj   +1 more source

Use of high resolution sonar for near-turbine fish observations (DIDSON) - We@Sea 2007-002 [PDF]

, 2010
In this study we investigate small scale distribution of pelagic fish within a windfarm by means of a high resolution sonar (DIDSON, Dual frequency IDentification SONar; Soundmetrics).
Burggraaf, D., Couperus, A.S., Keeken, O.A., van, Kooten, T., van, Tribuhl, S.V., Winter, H.V.   +5 more
core   +1 more source

Improving Sonar Image Patch Matching via Deep Learning

, 2017
Matching sonar images with high accuracy has been a problem for a long time, as sonar images are inherently hard to model due to reflections, noise and viewpoint dependence.
Valdenegro-Toro, Matias
core   +1 more source

QiandaoEar22: a high-quality noise dataset for identifying specific ship from multiple underwater acoustic targets using ship-radiated noise

EURASIP Journal on Advances in Signal Processing
Target identification of ship-radiated noise is a crucial area in underwater target recognition. However, there is currently a lack of multi-target ship datasets that accurately represent real-world underwater acoustic conditions.
Xiaoyang Du, Feng Hong
doaj   +1 more source

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications [PDF]

, 2014
Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves.
Alsheikh, Mohammad Abu, Lin, Shaowei, Niyato, Dusit, Tan, Hwee-Pink   +3 more
core   +3 more sources

Feature Selection of Scale Target Recognition by Underwater Acoustic Homing Weapons Based on Random Forest

水下无人系统学报
When underwater acoustic homing weapons identify underwater scale targets, it is necessary to extract different dimensional features from underwater target echoes and combine the features to form a complementary feature set to improve the recognition ...
Jianjing DENG, Lei SHI, Chenyu WANG, Liwen LIU, Xiangfeng YANG, Yunchuan YANG   +5 more
doaj   +1 more source

SKANN: Selective Kernel Audio Neural Networks for Underwater Mixed Ship Event Detection

CAAI Transactions on Intelligence Technology
Underwater acoustic target recognition (UATR) has become increasingly prevalent for ocean detection, localisation, and identification. However, due to the complexity and variability of underwater environments, especially in multi ship event environments,
Chun Shan, Tongyi Zou, Lingjun Zhao, Qinnan Zhang, Yafeng Zhu, Guizani Mohsen, Jing Qiu   +6 more
doaj   +1 more source

Sensor-Assisted Video Mosaicing for Seafloor Mapping [PDF]

, 2001
This paper discusses a proposed processing technique for combining video imagery with auxiliary sensor information. The latter greatly simplifies image processing by reducing complexity of the transformation model.
Cutter, Randy G, Jr., Huff, Lloyd C, Rzhanov, Yuri   +2 more
core   +1 more source

Mobile_ViT: Underwater Acoustic Target Recognition Method Based on Local–Global Feature Fusion

Journal of Marine Science and Engineering
To overcome the challenges of inadequate representation and ineffective information exchange stemming from feature homogenization in underwater acoustic target recognition, we introduce a hybrid network named Mobile_ViT, which synergizes MobileNet and ...
Haiyang Yao, Tian Gao, Yong Wang, Haiyan Wang, Xiao Chen   +4 more
semanticscholar   +1 more source

Multi-Task Mixture-of-Experts Model for Underwater Target Localization and Recognition

Remote Sensing
The scarcity of underwater acoustic data in deep and remote sea environments poses a significant challenge to data-driven target recognition models, severely restricting their performance. To address this challenge, this study presents a ray-theory-based
Peng Qian, Jingyi Wang, Yining Liu, Yingxuan Chen, Pengjiu Wang, Yanfa Deng, Peng Xiao, Zhenglin Li   +7 more
doaj   +1 more source