首页|Findings on Machine Learning Discussed by Investigators at Autonomous University of Baja California (Data-drive-based Machine Learning and Singular Spectrum Ana lysis To Identify Optical Patterns In Harsh Environments)
Findings on Machine Learning Discussed by Investigators at Autonomous University of Baja California (Data-drive-based Machine Learning and Singular Spectrum Ana lysis To Identify Optical Patterns In Harsh Environments)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news originating from Mexicali, Mexico, by N ewsRx correspondents, research stated, “This article proposes an enhancement of a singular spectrum analysis (SSA) technique based on Hilbert matrix (SSA-H) for autonomous navigation systems in a harsh environment. SSA is a technique that h as caught the attention of different fields and is used to extract trends and pa tterns in the time series domain.” Our news journalists obtained a quote from the research from the Autonomous Univ ersity of Baja California, “In this work, SSA-H is used to transform raw optical signals into meaningful information to build machine learning (ML) models. A te chnical vision system (TVS) with laser scanning for depth measurements is presen ted. According to the implementation of the TVS outdoors, some particular issues , such as interference radiation detected by its photodiode, can affect the syst em’s performance in determining depth measurements. This research extracts the l aser beam patterns in a real environment to create ML models to solve the proble m and address some of the technical challenges in a real environment. The main c ontribution of this work is designing an ML framework for recognizing the laser beam of the TVS based on SSA-H. Furthermore, a comparative analysis of ML techni ques to discriminate sunlight interference was studied and compared with differe nt configurations of SSA known in the literature.”
MexicaliMexicoNorth and Central Amer icaCyborgsEmerging TechnologiesMachine LearningAutonomous University of Baja California
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