Obtaining three-dimensional trajectory of multiple fish in water tank via video tracking
Sign Up to like & getrecommendations! Published in 2018 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-018-5755-5
Abstract: Accurately and reliably obtaining the three-dimensional motion data of individuals in fish schools is not only valuable for fish behaviour analysis and hydrodynamics studies but also be helpful in areas such as bio-inspired robot design.… read more here.
Keywords: three dimensional; dimensional trajectory; method; video tracking ... See more keywords
Three-Dimensional Trajectory Tracking Control of Underactuated Autonomous Underwater Vehicles with Input Saturation
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Shanghai Jiaotong University (Science)"
DOI: 10.1007/s12204-020-2195-y
Abstract: This paper addresses a three-dimensional (3D) trajectory tracking problem of underactuated autonomous underwater vehicles (AUVs) subjected to input saturation and external disturbances. The proposed controller can achieve practical convergence of tracking errors for general reference… read more here.
Keywords: three dimensional; underwater vehicles; dimensional trajectory; autonomous underwater ... See more keywords
Three‐dimensional trajectory tracking of an underactuated AUV based on fuzzy dynamic surface control
Sign Up to like & getrecommendations! Published in 2019 at "Iet Intelligent Transport Systems"
DOI: 10.1049/iet-its.2019.0347
Abstract: The three-dimensional trajectory tracking of an underactuated autonomous underwater vehicle (AUV) under the complex unknowns including model uncertainties and time-varying disturbances is studied. The reference pitch angle and yaw angle are designed in kinematics, based… read more here.
Keywords: three dimensional; trajectory; dimensional trajectory; tracking underactuated ... See more keywords
Low Dimensional Trajectory Hypothesis is True: DNNs Can Be Trained in Tiny Subspaces
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"
DOI: 10.1109/tpami.2022.3178101
Abstract: Deep neural networks (DNNs) usually contain massive parameters, but there is redundancy such that it is guessed that they could be trained in low-dimensional subspaces. In this paper, we propose a Dynamic Linear Dimensionality Reduction… read more here.
Keywords: true dnns; dimensional trajectory; trajectory hypothesis; dnns trained ... See more keywords