EXPLAINABLE AI FOR BEARING FAULT PROGNOSIS USING DEEP LEARNING TECHNIQUES


The processing of intimately familiar and unfamiliar voices: Specific neural responses of speaker recognition and identification.

Research has repeatedly shown that familiar and unfamiliar voices elicit different neural responses.But it has also been suggested that different neural correlates associate with the feeling of having heard a voice and knowing who the voice represents.The terminology used to designate these varying responses remains vague, creating a degree of conf

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Live 4D-OCT denoising with self-supervised deep learning

Abstract By providing three-dimensional visualization of tissues and instruments at high resolution, live volumetric optical coherence tomography (4D-OCT) has the potential to revolutionize ophthalmic surgery.However, the necessary imaging speed is accompanied by increased noise levels.A high data rate and the requirement for minimal latency impose

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Three-Dimensional Joint Inversion of the Resistivity Method and Time-Domain-Induced Polarization Based on the Cross-Gradient Constraints

The resistivity method and time-domain-induced polarization (TDIP) are two branches of electric exploration that are used to solve problems in mineral exploration, hydrogeology and engineering geology.In recent years, integrating different physical parameters for joint inversion to improve the accuracy of inversion results has been extensively exam

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Single minimum incision endoscopic radical nephrectomy for renal tumors with preoperative virtual navigation using 3D-CT volume-rendering

Abstract Background Single minimum incision endoscopic surgery (MIES) involves the use of a flexible high-definition laparoscope to facilitate open surgery.We reviewed our method of radical nephrectomy for renal tumors, which is single MIES combined with preoperative virtual surgery employing three-dimensional CT images reconstructed by the volume

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