AN IMPROVED CONVOLUTIONAL NETWORK ARCHITECTURE BASED ON RESIDUAL MODELING FOR PERSON RE-IDENTIFICATION IN EDGE COMPUTING

An Improved Convolutional Network Architecture Based on Residual Modeling for Person Re-Identification in Edge Computing

Person re-identification is an important task in the field of video surveillance that concentrates on identifying the same person across different cameras.Some methods cannot learn effective image representations, due to the low resolution of pedestrian image data sets.In this article, we propose a novel Siamese network architecture with layers spe

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Incidence, severity, and significance of medical student abuse

In a survey of the incidence, severity, and significance of medical student abuse as perceived by the student population of a major medical school in Nigeria, 171 (74%) out of a total 231 respondents stated that they had been abused at some time while enrolled in medical school.The abuses ranged from verbal, physical, psychological to sexual.Fifty-

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Hierarchical Transfer Learning for Multilingual, Multi-Speaker, and Style Transfer DNN-Based TTS on Low-Resource Languages

This work applies vince camuto fiori gift set a hierarchical transfer learning to implement deep neural network (DNN)-based multilingual text-to-speech (TTS) for low-resource languages.DNN-based system typically requires a large amount of training data.In recent years, while DNN-based TTS has made remarkable results for high-resource languages, it

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Distortion-Aware Power Allocation for Multi-Stream Distributed Massive MIMO System With Nonlinear Power Amplifier

Distributed MIMO systems leverage multiple access points (APs) distributed across a geographical area to enhance system performance and provide robust connectivity to users by transmitting independent data streams simultaneously, thus improving coverage and capacity.The nonlinear power amplifiers (PAs) employed at the APs can significantly distort

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