Following the success of the previous editions at WCCI 2018 (Rio de Janeiro, Brazil) and CEC/GECCO 2019 (New Zealand and Prague, Czechia) we are launching a more challenging algorithm competition at major international conferences in the field of computational intelligence. This WCCI & GECCO 2020 competition proposes two testbeds in the energy domain:

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Following the success of the previous editions (CEC, GECCO, WCCI), we are launching a more challenging competition at major conferences in the field of computational intelligence. This GECCO 2021 competition proposes two tracks in the energy domain:

Last Updated On: 
Wed, 02/24/2021 - 10:38
Citation Author(s): 
Fernando Lezama, Joao Soares, Bruno Canizes, Zita Vale, Ruben Romero

The dataset consists of the ISFET sensor data utilized to train ML models for drift compensation.

Instructions: 

This dataset consists of the sensor data used to develop SPICE macro model of ISFET and associated documentation.

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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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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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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 Horses Detection Database (THDD Database) 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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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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208 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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118 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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210 Views

Anxiety affects human capabilities and behavior as much as it affects productivity and quality of life. It can be considered as the main cause of depression and suicide. Anxious states are easily detectable by humans due to their acquired cognition, humans interpret the interlocutor’s tone of speech, gesture, facial expressions and recognize their mental state. There is a need for non-invasive reliable techniques that perform the complex task of anxiety detection.

Instructions: 

Download Zip file and extract it.

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