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Abolghasem Sadeghi-Niaraki

Researcher at K.N.Toosi University of Technology

Publications -  95
Citations -  1353

Abolghasem Sadeghi-Niaraki is an academic researcher from K.N.Toosi University of Technology. The author has contributed to research in topics: Computer science & Geographic information system. The author has an hindex of 13, co-authored 75 publications receiving 670 citations. Previous affiliations of Abolghasem Sadeghi-Niaraki include Inha University & Sejong University.

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Deep Learning Approach for Short-Term Stock Trends Prediction Based on Two-Stream Gated Recurrent Unit Network

TL;DR: A novel framework to predict the directions of stock prices by using both financial news and sentiment dictionary is proposed and outperforms state-of-the-art models and is more efficient in dealing with financial datasets.
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A Review on Mixed Reality: Current Trends, Challenges and Prospects

TL;DR: This review studies intensive research to obtain a comprehensive framework for Mixed reality applications and introduces MR development steps and analytical models, a simulation toolkit, system types, and architecture types, in addition to practical issues for stakeholders such as considering MR different domains.
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Crop pest recognition in natural scenes using convolutional neural networks

TL;DR: A crop pest recognition method that accurately recognizes ten common species of crop pests by applying several deep convolutional neural networks (CNNs) has the potential to be applied in real-world applications and further motivate research on crop disease identification.
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A methodological framework for assessment of ubiquitous cities using ANP and DEMATEL methods

TL;DR: An effective framework to determine the required platform toward establishing a u-city is developed by explores the main components of a smart city, such as citizens, environments, and key infrastructures, and the criteria to measure each component, and a ubiquitous coefficient for a city is proposed.
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Real world representation of a road network for route planning in GIS

TL;DR: This study investigates how a road network can represent the real world in a GIS and offer route planning tools and proposes an impedance model (IM) using the analytical hierarchical process (AHP) method, which was successfully implemented in this work.