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/

الانترنت

https://ieeexplore.ieee.org/document/8695734/

مواد مشابهة