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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94 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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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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263 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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66 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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84 Views

The data collection was carried out over several months and across several cities including but not limited to Quetta, Islamabad and Karachi, Pakistan. Ultimately, the number of images collected as part of the Pakistani dataset were, albeit in a very small quantity. The images taken were also distributed across the classes unevenly, just like the German dataset. All the 359 images were then manually cropped to filter out the unwanted image background data. All the images were sorted into folders with names corresponding to the label of the images.

Instructions: 

Dataset is divided by classes and the images inside the folder are named randomly and contain no useful labels in their names.

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116 Views

We study the ability of neural networks to steer or control trajectories of dynamical systems on graphs, which we represent with neural ordinary differential equations (neural ODEs). To do so, we introduce a neural-ODE control (NODEC) framework and find that it can learn control signals that drive graph dynamical systems into desired target states. While we use loss functions that do not constrain the control energy, our results show that NODEC produces control signals that are highly correlated with optimal (or minimum energy) control signals.

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Retinal Fundus Multi-disease Image Dataset (RFMiD) consisting of a wide variety of pathological conditions. 

Instructions: 

Detailed instructions about this dataset are available on the challenge website: https://riadd.grand-challenge.org/.

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433 Views

Predicting energy consumption is currently a key challenge for the energy industry as a whole.  Predicting the consumption in a certain area is massively complicated due to the sudden changes in the way that energy is being consumed and generated at the current point in time. However, this prediction becomes extremely necessary to minimise costs and to enable adjusting (automatically) the production of energy and better balance the load between different energy sources.

Last Updated On: 
Wed, 12/23/2020 - 12:16
Citation Author(s): 
Isaac Triguero

This dataset brings some problem sets and results from some classical algorithms from the evolutionary computational community.

We have used some tools: Pymoo, Platypus and Pagmo

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71 Views

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