Deep learning for hydrophone big data
WebOct 31, 2024 · Deep Learning for DOA Estimation Using a Vector Hydrophone. Abstract: Source azimuth can be estimated via the complex sound intensity method based on a … WebDec 19, 2024 · Detecting and classifying ships based on radiated noise provide practical guidelines for the reduction of underwater noise footprint of shipping. In this paper, the detection and classification are implemented by auditory inspired convolutional neural networks trained from raw underwater acoustic si …
Deep learning for hydrophone big data
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WebApr 23, 2024 · Four deep learning CNN models were trained (see below); the final detector is an ensemble of these four models. Model 1: Built a CNN from scratch using AlexNet architecture. Model 2: Transfer learning with fine-tuning from a pre-trained VGG16 model. Model 3: Transfer learning with fine-tuning from a pre-trained ResNet50 model. WebShip noise observation is of great significance to marine environment research and national defense security. Acoustic stealth technology makes a variety of ship noise significantly reduced, which is a new challenge for marine noise monitoring. However, there are few high spatial gain detection methods for low-noise ship monitoring. Therefore, a high Signal-to …
WebMar 9, 2024 · Shorten and T. M. Khoshgoftaar, “ A survey on image data augmentation for deep learning,” J. Big Data 6(1), 1 ... (ACF) from a single hydrophone in the deep ocean is proposed in this letter. Instead of extracting the multi-path time delays, the ACF-NET directly uses the ACFs for source range and depth estimation. ... WebMay 16, 2014 · Deep learning is currently an extremely active research area in machine learning and pattern recognition society. It has gained huge successes in a broad area of applications such as speech recognition, computer vision, and natural language processing. With the sheer size of data available today, big data brings big opportunities and …
WebMay 1, 2024 · 1. Introduction. In this fast-growing digital world, Big Data and Deep learning are the high attention of data science. Big Data is the collection of huge amount of digital raw data that is difficult to manage and analyse using traditional tools [1], [2].As the digital data is growing exponentially in different shapes, formats and sizes, therefore it is very … WebJan 10, 2024 · Fueled by enterprises seeking greater insight from their analytics, deep learning is now seeing widespread adoption. While this artificial intelligence (AI) discipline was first conceived in the late 1950s, …
WebAug 1, 2024 · In this proposed scheme, deep learning feature sets are adopted and processed by a support vector machione (SVM) classifier, which outperforms the MFCC-based method. This paper presents an efficient deep learning framework for long-term monitoring of acoustic events from hydrophone big data. The large-scale noisy ONC …
WebAug 5, 2024 · deep learning from its superset machine learning is the use of multilayer models which leads to a higher-level representation of the underlying data sources … microfiber fiber contentWebOct 1, 2024 · In this paper, we propose a data fusion algorithm based on the weighted histogram statistics (DF-WHS) to improve the performance of direction-of-arrival (DOA) estimation for the vector hydrophone vertical array (VHVA). The processing frequency band is firstly divided into multiple sub-bands, and the high-resolution multiple signal … microfiber faux leather fabric yardWebThe Pioneer Seamount Acoustic Observatory is the first deep-water civilian (non-classified) hydrophone array for long-term monitoring of ambient ocean noises and their effects on the marine environment. The array consists of four hydrophone elements suspended vertically in the water above the sea floor. microfiber eyeglass lens cleaning clothsWebAug 1, 2024 · This paper presents an efficient deep learning framework for long-term monitoring of acoustic events from hydrophone big data. The large-scale noisy ONC … the orchard company wikipediaWebOct 31, 2024 · Abstract: Source azimuth can be estimated via the complex sound intensity method based on a single vector hydrophone, which exploits the physical properties of acoustic pressure and particle velocity components. Deep learning has been successfully used to estimate source depth and distance via training and prediction; herein it is … the orchard counselling servicethe orchard day nursery chellastonWebA deep learning approach based on big data is proposed to locate broadband acoustic sources using a single hydrophone in ocean waveguides with uncertain bottom … the orchard david wilson