MOTION LEARNING USING SPATIO-TEMPORAL NEURAL NETWORK

MOTION LEARNING USING SPATIO-TEMPORAL NEURAL NETWORK

Motion trajectory prediction is one of the key areas in behaviour and surveillance studies.Many related successful applications have been reported in the literature.However, Packing Materials most of the studiesare based on sigmoidal neural networks in which some dynamic properties of the data are overlooked due to the absence of spatiotemporal enc

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Assement the long-term relationship between the economic policy uncertainty and the excess returns of various industries index

In the past few years, several major domestics and international challenges have emerged, causing global political and economic uncertainty.Economic uncertainty, defined as the difficulty in predicting the economic environment, arises from various factors such as political instability, changes and uncertainties in government policies, natural disas

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Exercise after breast cancer treatment: current perspectives

Christina M Dieli-Conwright, Breanna Z Orozco Division of Biokinesiology and Physical Therapy, Women's Health and Exercise Laboratory, University of Southern California, Los Angeles, CA, USA Abstract: Over the past 2 decades, great strides have been made in the field of exercise-oncology research, particularly with breast cancer.This area of re

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Application of Endophytic Pseudomonas fluorescens and a Bacterial Consortium to Brassica napus Can Increase Plant Height and Biomass under Greenhouse and Field Conditions

Plant associated bacteria with plant growth promotion (PGP) properties have been proposed for use as environmentally friendly biofertilizers for sustainable agriculture; however, analysis of their efficacy in the field is often limited.In this study, greenhouse and field trials were carried out using individual endophytic Pseudomonas fluorescens st

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