TSViz: Demystification of Deep Learning Models for Time-Series Analysis

TSViz: Demystification of Deep Learning Models for Time-Series Analysis

This paper presents a novel framework for the demystification of convolutional deep learning models for time-series analysis. This is a step toward making informed/explainable decisions in the domain of time series, powered by deep learning. There have been numerous efforts to increase the interpret...

وصف كامل

التفاصيل البيبلوغرافية
المؤلفون الرئيسيون:	Shoaib Ahmed Siddiqui, Dominique Mercier, Mohsin Munir, Andreas Dengel, Sheraz Ahmed
التنسيق:	مقال
اللغة:	English
منشور في:	IEEE 2019-01-01
سلاسل:	IEEE Access
الموضوعات:	Deep learning representation learning convolutional neural networks time-series analysis time-series forecasting feature importance
الوصول للمادة أونلاين:	https://ieeexplore.ieee.org/document/8695734/

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