Results 51 to 60 of about 4,375,078 (278)

An Effective Method for Underwater Biological Multi-Target Detection Using Mask Region-Based Convolutional Neural Network

, 2023
Underwater creatures play a vital role in maintaining the delicate balance of the ocean ecosystem. In recent years, machine learning methods have been developed to identify underwater biologicals in the complex underwater environment.
Zhaoxin Yue, Zhe Chen, Bing Yan, Huaizhi Liu   +3 more
core   +1 more source

Competitive Deep-Belief Networks for Underwater Acoustic Target Recognition [PDF]

Sensors, 2018
Underwater acoustic target recognition based on ship-radiated noise belongs to the small-sample-size recognition problems. A competitive deep-belief network is proposed to learn features with more discriminative information from labeled and unlabeled samples.
Honghui Yang, Sheng Shen 0004, Xiaohui Yao, Meiping Sheng, Chen Wang   +4 more
openaire   +2 more sources

Gradient‐Conductivity Architecture Enables Synchronous Enhancement of Sensitivity and Detection Range in Multifunctional All‐Paper Sensors

Advanced Functional Materials, EarlyView.
A gradient‐engineered all‐paper sensor is fabricated by integrating MXene and in situ grown AgNPs within hierarchical cellulose networks. The device breaks the sensitivity–detection range trade‐off through cascaded conductive pathways, enabling ultrahigh pressure sensitivity, humidity–pressure decoupled dual‐mode sensing, and outstanding EMI shielding,
Ao Li, Jun Xu, Dezhong Xu, Zhaohui Zhang, Jiyi Li, Daxian Cao, Kefu Chen, Mizi Fan   +7 more
wiley   +1 more source

Microscale Patterning of Ultrahigh‐Viscosity Metallic‐Polymer Composites via Embedded Droplet Writing

Advanced Functional Materials, EarlyView.
A hybrid additive manufacturing platform integrates direct droplet writing of metallic composite with VAT photopolymerization to fabricate architected soft magnetic composites. This approach enables microscale patterning of high‐viscosity materials for programmable actuators, adaptive fluidic devices, and switchable adhesives, offering tunable ...
Yeowon Yoon, Jian Ni, Sungmo Park, Yang Xu, Yong Chen   +4 more
wiley   +1 more source

Optimizing NiMo Electrocatalyst Coatings for Hydrogen Evolution in Alkaline Electrolysis With The Machine Learning‐Guided Autonomous Platform CatBot

Advanced Functional Materials, EarlyView.
This work presents a closed‐loop optimization workflow integrating CatBot, an automated synthesis and testing system, to discover NiMo hydrogen‐evolution catalysts. CatBot synthesised and evaluated 228 unique samples, identifying the best performing catalysts for transfer to nickel‐foam electrodes. The best candidate is highly active, reaching 1 Acm−2${
Paolo Vincenzo Freiesleben de Blasio, Jonas Elsborg, Elif Coşkun, Andreas Burger, Pradipkumar Manubhai Leuaa, Thu Pham Anh Phan, Jin Hyun Chang, Christodoulos Chatzichristodoulou   +7 more
wiley   +1 more source

Graph Embedding With Mel-Spectrograms for Underwater Acoustic Target Recognition

IEEE Journal of Oceanic Engineering
Underwater acoustic target recognition (UATR) is extremely challenging due to the complexity of ship-radiated noise and the variability of ocean environments. Although deep learning (DL) approaches have achieved promising results, most existing models implicitly assume that underwater acoustic data lie in a Euclidean space. This assumption, however, is
Sheng Feng, Shuqing Ma, Xiaoqian Zhu
openaire   +3 more sources

Structure‐Property Relationships in Catecholamine Coatings for Broad Surface Functionalization

Advanced Functional Materials, EarlyView.
Inspired by mussel adhesive proteins (MAPs), six catecholamine molecules with different molecular structure were systematically characterized and compared based on their ability to form homogeneous, reactive coatings. Highlighting candidates capable of balancing coating properties of interest, their successful use as primer layers for organic and ...
Caroline F. Harms, Qiming Li, Ye‐Sol Kim, Anish Tuteja, Jinsang Kim, Abdon Pena‐Francesch   +5 more
wiley   +1 more source

Research on Neuro-Acoustic Human–Machine Collaborative Inter-Domain Global Attention Fusion for Underwater Acoustic Target Recognition

Journal of Marine Science and Engineering
To enhance the adaptability of current underwater acoustic target recognition technology in complex marine environments and improve the performance of human–machine collaborative operations, this study proposes a human–machine collaborative underwater ...
Jiaqi Zhang, Zhangsong Shi, Huihui Xu, Zhe Rao, Songxue Bai, Junfeng Gao   +5 more
doaj   +1 more source

Biodegradable 3D‐Printable and Coatable Antifouling Composites for Marine Applications

Advanced Functional Materials, EarlyView.
Marine biofouling damages submerged surfaces and raises greenhouse gas emissions. Biodegradable antifouling biocomposites were developed by hot‐mixing beeswax, Tween 80, and calcium stearate or stearic acid. Adjusting the component ratio enables processing via hot‐pressing, 3D‐printing, or dip‐coating.
Gabriele Corigliano, Lorenzo Ravelli, Martina Nardi, Ruowen Tu, Elena Bellini, Valerio Isa, Carlo Filippeschi, Roberta Finazzi, Luca Ceseracciu, Niloofar Paknezhad, Vincenzo Scribano, Paolo Galli, Silvia Lavorano, Simone Montano, Barbara Mazzolai, Marco Contardi, Pietro Cataldi, Athanassia Athanassiou   +17 more
wiley   +1 more source

Geometry parameters recognition method for underwater target model based on Kriging surrogate model

Zhongguo Jianchuan Yanjiu
ObjectivesUnderwater target parameter recognition can provide the basis for target classification and recognition. To this end, an underwater target parameter recognition method based on the Kriging surrogate model is proposed.
Jiang LIU, Yansen LIU, Sheng LI
doaj   +1 more source