NONCONTACT SURFACE ROUGHNESS ESTIMATION USING 2D COMPLEX WAVELET ENHANCED RESNET FOR INTELLIGENT EVALUATION OF MILLED METAL SURFACE QUALITY

Noncontact Surface Roughness Estimation Using 2D Complex Wavelet Enhanced ResNet for Intelligent Evaluation of Milled Metal Surface Quality

Machined surfaces are rough from a microscopic perspective no matter how finely they are finished.Surface roughness is an important factor to consider during production quality control.Using modern techniques, surface roughness measurements are beneficial for improving machining quality.With optical imaging of machined surfaces as input, a convolut

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Analysis of the Grid Quantization for the Microwave Radar Coincidence Imaging Based on Basic Correlation Algorithm

Samsung RB33N321NSS/EU Frost Free Fridge Freezer - S/Steel In Microwave Radar Coincidence Imaging (MRCI), the imaging region is typically discretized into a fine grid.In other words, it assumes that the equivalent scatterers of the target are precisely located at the centers of these pre-discretized grids.However, this approach usually encounters t

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Effects of transcutaneous electric acupoint stimulation on drug use and responses to cue-induced craving: a pilot study

Abstract Background Transcutaneous electric acupoint stimulation (TEAS) avoids the use of needles, and instead delivers a mild electric current at traditional acupoints.This technique has been used for treating heroin addiction, but has not been systematically tested for other drugs of abuse.This study aims to investigate the effects of TEAS on dru

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Soft Pneumatic Actuators for Rehabilitation

Pneumatic artificial muscles are pneumatic devices with practical and various applications as common actuators.They, as human muscles, work in agonistic-antagonistic way, giving a traction force only when supplied by compressed air.The state of the art of soft pneumatic actuators is here analyzed: different models of pneumatic muscles are considere

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Pruning Adapters with Lottery Ticket

Massively pre-trained transformer models such as BERT have gained great success in many downstream NLP tasks.However, they are computationally expensive to fine-tune, slow for inference, and have large storage requirements.So, transfer learning with adapter modules has been introduced and has become a remarkable solution for those problems.Neverthe

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