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This dataset is a collection of images and their respective labels containing multiple Indian coins of different denominations and their variations. The dataset only contains images of one side of each coin (Tail side) which contains the denomination value.
The samples were collected with the help of a mobile phone while the coins were placed on top of a white sheet of A4-sized paper.
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The dataset consists of two classes: COVID-19 cases and Healthy cases
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An offline handwritten signature dataset from two most popular scripts in India namely Roman and Devanagari is proposed here.
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Lung segmentation is essential in developing AI-assisted diagnosis methods. Here is the result of lung segmentation using morphological operation, and it has been used in our study. It contains 7053 CT slices in .jpg format. And the original dataset can be seen via the Kaggle link https://www.kaggle.com/hgunraj/covidxct
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We have developed this dataset for the Bangla image caption. Here, we have recorded 500 images with one caption of each. Basically the lifestyle, festivals are mainly focused in this dataset. We have accomplished rice/harvest festivals, snake charming, palanquin, merry-go-round, slum, blacksmith, potter, fisherman, tat shilpo, jamdani, shutki chash, date juice, hal chash, tokai, pohela falgun, gaye holud, etc.
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Datasets as described in the research paper "Intrusion Detection using Network Traffic Profiling and Machine Learning for IoT Applications".
There are two main dataset provided here, firstly is the data relating to the initial training of the machine learning module for both normal and malicious traffic, these are in binary visulisation format, compresed into the document traffic-dataset.zip.
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