YonseiStressImageDatabase is a database built for image-based stress recognition research. We designed an experimental scenario consisting of steps that cause or do not cause stress; Native Language Script Reading, Native Language Interview, Non-native Language Script Reading, Non-native Language Interview. And during the experiment, the subjects were photographed with Kinect v2. We cannot disclose the original image due to privacy issues, so we release feature maps obtained by passing through the network.

Instructions: 

 

Database Structure

- YonseiStressImageDatabase

         - Subject Number (01~50)

                  - Data acquisition phase

                    (Native Language Script Reading, Native Language Interview, Non-native Language Script Reading, Non-native Language Interview)

                           - Data (*.npy, the filename is set to the time the data was acquired; YYYYMMDD_hhmmss_ms)

 

In the case 'Non-native_Language_Interview' data of subject 26, it was not acquired due to equipment problems.

 

Citing YonseiStressImageDatabase

If you use YonseiStressImageDatabase in a scientific publication, we would appreciate references to the following paper:

Now Reviewing.

 

Usage Policy

Copyright © 2019 AI Hub, Inc., https://aihub.or.kr/

AI data provided by AI Hub was built as part of a business National Information Society Agency's 'Intelligent information industry infrastructure construction project' in Korea, and the ownership of this database belongs to National Information Society Agency.

Specialized field AI data was built for artificial intelligence technology development and prototype production and can be used for research purposes in various fields such as intelligent services and chatbots.

 

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356 Views

Given the difficulty to handle planetary data we provide downloadable files in PNG format from the missions Chang'E-3 and Chang'E-4. In addition to a set of scripts to do the conversion given a different PDS4 Dataset.

Instructions: 

Please see Readme inside ZIP files for more information about the provided data and scripts. 

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149 Views

Animal recognition is an active research topic in recent years. Horse’s recognition is an important task in the world and  in  order  to  promote  horse’s  recognition  research,  the  Tunisian  Research  Groups  in  Intelligent  Machines  of University of Sfax (REGIM of Sfax) will provide the Tunisian Horses DataBase of Regim Lab’2015 (THoDBRL’2015) freely of charge to mainly horses’ face recognition researchers and to increase total of researches done to enhance animal recognition. This Database is used in [1].

Instructions: 

Download Zip file and extract it.

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196 Views

Animal detection is an active research topic in recent years. Horse’s face detection is an important task in the world and in order to promote horse’s detection and recognition research, the REGIM-Lab.: REsearch Groups in Intelligent Machines, ENIS, University of Sfax, Tunisia will provide the Tunisian Horse Detection Database (THDD) freely of charge to mainly horses’ face detection researchers and to increase total of researches done to enhance animal detection.

Instructions: 

Download Zip file and extract it.

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146 Views

Social images analysis from social networks is considered as one of the most popular social technologies. Social images analysis is an active research topic in recent years and in order to promotes social images’s analysis research, the REGIM-Lab.: REsearch Groups in Intelligent Machines, ENIS, University of Sfax, Tunisia provides the SmartCityZen database’2016 freely of charge to social images analysis researchers.

Instructions: 

Download Zip file and extract it.

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266 Views

Social images analysis from social networks is considered as one of the most popular social technologies. Social images analysis is an active research topic in recent years and in order to promotes social images’s analysis research, the REGIM-Lab.: REsearch Groups in Intelligent Machines, ENIS, University of Sfax, Tunisia provides the Sm@rtCityZen social images database freely of charge to social images analysis researchers.

Instructions: 

Download Zip file and extract it.

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173 Views

Biometric-based hand modality is considered as one of the most popular biometric technologies especially in forensic applications. Hand recognition is an active research topic in recent years and in order to promote hand’s recognition research, the REGIM-Lab.: REsearch Groups in Intelligent Machines, ENIS, University of Sfax, Tunisia provides the REgim Sfax Tunisian hand database (REST database) freely of charge to mainly hand and palmprint recognition researchers.

Instructions: 

Download Zip file and extract it.

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337 Views

Character recognition has been widely understood as a means of mechanizing the process of understanding text in the written form to facilitate fast and efficient use of text. Indeed, text existing all around us presents information for peoples. However, tourists in foreign countries are unable to understand what indicate text on road signs, shop names, product advertisements, posters, etc. when they are unfamiliar with the native language of the visited country.

Instructions: 

Download Zip file and extract it.

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340 Views

The ADAB database (The Arabic handwriting Data Base) was developed to advance the research and development of Arabic on-line handwritten systems. This database is developed in cooperation between the Institut fuer Nachrichtentechnik (IfN) and Research Groups in Intelligent Machines, University of Sfax, Tunisia. The text written is from 937 Tunisian town/village names. A pre-label assigned to each file consists of the postcode in a sequence of Numeric Character References, which stored in the UPX file format.

Instructions: 

Download Zip file and extract it.

A pre-label assigned to each file consists of the postcode in a sequence of Numeric Character References, which stored in the UPX file format. 

An InkML file including trajectory information and a plot image of the word trajectory are also generated. 

Additional information about the writer can also be provided.

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259 Views

The dataset consists all the Telugu characters that contains Vowels, Consonants and combine characters such as Othulu (Consonant-Consonant) and Guninthamulu (Consonant-Volwels). The main objective of this dataset to recognize handwritten Telugu characters, from that convert handwritten document into editable electronic copy.

Instructions: 

All the images are in the same size and all images are scanned by scanner and segmented manually and all images are jpeg images.

 Acknowledgement:

 The work is carried out under Collaborative Research Project Sponsored by JNTU Hyderabad, India. The project file no. JNTUH/TEQIP-III/CRS/2019/CSE/12 and Titled as "Deep Learning Aided-OCR for Handwritten Telugu Character".

 

 

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1004 Views

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