Results 21 to 30 of about 20,966 (203)

Bistatic Localization of Objects in Very Shallow Water

IEEE Access, 2019
Bistatic or multi-static systems use spatially distributed sources and/or receivers to ensonify scattering objects over a distance to obtain the acoustic images of individual targets for classification purposes. The targets need to be localized first and
Ting Zhang, T. C. Yang, Wen Xu
doaj   +1 more source

Active Classification: Theory and Application to Underwater Inspection [PDF]

, 2011
We discuss the problem in which an autonomous vehicle must classify an object based on multiple views. We focus on the active classification setting, where the vehicle controls which views to select to best perform the classification.
Hollinger, Geoffrey A., Mitra, Urbashi, Sukhatme, Gaurav S.   +2 more
core   +2 more sources

Target-depth estimation in active sonar

, 2016
International audienceIn active sonar, the objectives are to detect, localize and classify an underwater target. Azimuth and range are often used in anti-submarine warfare to localize targets.
Doisy, Yves, Ioana, Cornel, Josso, Nicolas, Mars, Jerome,, Mours, Alexis   +4 more
core   +4 more sources

Radar and RGB-depth sensors for fall detection: a review [PDF]

, 2017
This paper reviews recent works in the literature on the use of systems based on radar and RGB-Depth (RGB-D) sensors for fall detection, and discusses outstanding research challenges and trends related to this research field.
Cippitelli, Enea, Fioranelli, Francesco, Gambi, Ennio, Spinsante, Susanna   +3 more
core   +1 more source

Deep Learning Methods for Assessing Time‐Variant Nonlinear Signatures in Clutter Echoes

Advanced Intelligent Systems, EarlyView.
Motion classification from biosonar echoes in clutter presents a fundamental challenge: extracting structured information from stochastic interference. Deep learning successfully discriminates object speed and direction from bat‐inspired signals, achieving 97% accuracy with frequency‐modulated calls but only 48% with constant‐frequency tones. This work
Ibrahim Eshera, Gaurav Duggal, Rolf Müller   +2 more
wiley   +1 more source

Active sonar target recognition method based on multi‐domain transformations and attention‐based fusion network

IET Radar, Sonar & Navigation
The classification and recognition of underwater targets by an active sonar system remain challenging and complex. Traditional methods have limited classification performance in time and spatially varying ocean channels.
Qingcui Wang, Shuanping Du, Wei Zhang, Fangyong Wang   +3 more
doaj   +1 more source

Effective Data Augmentation for Active Sonar Classification Using Attention-Based Complementary Learning With Uncertainty Measure

IEEE Access
We enhance the performance of active sonar classification by integrating a validated attention-based complementary learning model (ABCL) with an active learning (AL) framework, following modifications to adapt the model for AL.
Youngsang Hwang, Geunhwan Kim, Wooyoung Hong, Youngmin Choo   +3 more
doaj   +1 more source

Fitness Activity Recognition on Smartphones Using Doppler Measurements

Informatics, 2018
Quantified Self has seen an increased interest in recent years, with devices including smartwatches, smartphones, or other wearables that allow you to monitor your fitness level.
Biying Fu, Florian Kirchbuchner, Arjan Kuijper, Andreas Braun, Dinesh Vaithyalingam Gangatharan   +4 more
doaj   +1 more source

Applying a Systems Thinking Approach to Circular Economy Transitions: Insights From the Use of a Sociotechnical Systems Approach Within the UK Hospitality Sector

Business Strategy and the Environment, EarlyView.
ABSTRACT Despite more than 20 years of research into sustainable tourism, the environmental impact of the UK hospitality sector remains high. A growing body of research into the concept of a circular economy (CE) demonstrates that transitioning to this way of working has significant benefits both for the environment and business outcomes.
Danielle Farrow, Hannah Collis, Fiona Charnley   +2 more
wiley   +1 more source

Data augmentation based on highlight image models of underwater maneuvering target

Xibei Gongye Daxue Xuebao
With the development of underwater acoustic countermeasure technology, deep learning is applied to recognize echo geometry features of underwater targets, but it faces the problem of sample scarcity.
LIU Xiaochun, YANG Yunchuan, HU Youfeng, YANG Xiangfeng, LI Yongsheng, XIAO Lin   +5 more
doaj   +1 more source