The role of news sentiment in oil futures returns and volatility forecasting: Data-decomposition based deep learning approach

This paper discusses the importance of the students ‘character building in the level of primary school/Islamic elementary school to face the globalization and information era. Education is the process of determining the nation’s character. Good or bad character of the nation in the future will be determined by the present quality of education. Building the character through Tahfidzul Quran learning approach is expected to be the main foundation to improve the degree and prestige of learners as the asset of the nation. This study aimed to describe the process of Tahfidzul Quran learning which included planning, organizing, doing action and monitoring the important role of learning itself to build the learners’ character, especially in Madrasah Ibtidaiyah Istiqomah Sambas Purbalingga.

Download Full-text

Comparison of various Activation Functions A Deep Learning Approach

International Journal of Computer Sciences and Engineering ◽

10.26438/ijcse/v6i3.122126 ◽

2018 ◽

Vol 6 (3) ◽

pp. 122-126

Author(s):

Mohammed Ibrahim Khan ◽

◽

Akansha Singh ◽

Anand Handa ◽

◽

...

Keyword(s):

Deep Learning ◽

Learning Approach ◽

Activation Functions

Download Full-text

A Deep Learning based Arabic Script Recognition System: Benchmark on KHAT

The International Arab Journal of Information Technology ◽

10.34028/iajit/17/3/3 ◽

2020 ◽

Vol 17 (3) ◽

pp. 299-305 ◽

Cited By ~ 1

Author(s):

Riaz Ahmad ◽

Saeeda Naz ◽

Muhammad Afzal ◽

Sheikh Rashid ◽

Marcus Liwicki ◽

...

Keyword(s):

Deep Learning ◽

Character Recognition ◽

Data Augmentation ◽

Short Term Memory ◽

Recognition System ◽

Learning Approach ◽

Arabic Text ◽

Data Set ◽

Processing Step ◽

Handwritten Arabic

This paper presents a deep learning benchmark on a complex dataset known as KFUPM Handwritten Arabic TexT (KHATT). The KHATT data-set consists of complex patterns of handwritten Arabic text-lines. This paper contributes mainly in three aspects i.e., (1) pre-processing, (2) deep learning based approach, and (3) data-augmentation. The pre-processing step includes pruning of white extra spaces plus de-skewing the skewed text-lines. We deploy a deep learning approach based on Multi-Dimensional Long Short-Term Memory (MDLSTM) networks and Connectionist Temporal Classification (CTC). The MDLSTM has the advantage of scanning the Arabic text-lines in all directions (horizontal and vertical) to cover dots, diacritics, strokes and fine inflammation. The data-augmentation with a deep learning approach proves to achieve better and promising improvement in results by gaining 80.02% Character Recognition (CR) over 75.08% as baseline.

Download Full-text