Machine Learning

This peach tree disease detection dataset is a multimodal, multi-angle dataset which was constructed for monitoring the growth of peach trees, including stress analysis and prediction. An orchard of peach trees is considered in the area of Thessaly, where 889 peach trees were recorded in a full crop season starting from Jul. 2021 to Sep. 2022. The dataset includes a) aerial / Unmanned Aerial Vehicle (UAV) images, b) ground RGB images/photos, and c) ground multispectral images/photos.

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This dataset contains data on drone reflectance, aphid survey data, and different aphid treatments for 288 points.

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Insecurity is a problem that affects all cities around the world to a greater or lesser extent, and some of them make use of video surveillance to combat it, setting up monitoring centres with hundreds of cameras. For the most part, these centres are staffed by personnel responsible for observation and incident response. The advancement of technology in the market offers the possibility to optimise and add value to these processes.

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In the digital era of the Industrial Internet of Things (IIoT), the conventional Critical Infrastructures (CIs) are transformed into smart environments with multiple benefits, such as pervasive control, self-monitoring and self-healing. However, this evolution is characterised by several cyberthreats due to the necessary presence of insecure technologies. DNP3 is an industrial communication protocol which is widely adopted in the CIs of the US. In particular, DNP3 allows the remote communication between Industrial Control Systems (ICS) and Supervisory Control and Data Acquisition (SCADA).

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This Dataset is related to the data prices of the cryptocurrency "Ethereum" over four years, from 01/01/2018 to 114/22/2022. Also, the new dataset created by the predictions of the intelligent filtered LSTM model is included.

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This paper presents a digital image dataset of historical handwritten birth records stored in the archives of several parishes
across Sweden, together with the corresponding metadata that supports the evaluation of document analysis algorithms’

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This dataset is the outcome of an observation on Hyssop germination under Lead (Pb) tension and Gixberlin Acid based hormonal priming. Pb tension levels are 0, 25, 50,75, and 100 mg/L, respectively in this study. Gixberlin acid priming is done under 0, 50,100, 150, and 200 mg/L and each scenario is repeated four times during this study. Mean Germination Time (MGT), Root Length( RL) and Shoot Length (SL) have been measured.  Moreover, different enzyme levels including superoxide dismutase, catalase, ascorbate peroxidase, and Guaiacol Peroxidase. 

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The greenhouse remote sensing image dataset we produced contains 2101 tiles and 23914 greenhouses. And in the data set, 37.9% of dense scenes were added, so that the model trained through this data set could better adapt to the dense scene detection task.

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The addy Doctor dataset contains 16,225 labeled paddy leaf images across 13 classes (12 different paddy diseases and healthy leaves). It is the largest expert-annotated visual image dataset to experiment with and benchmark computer vision algorithms. The paddy leaf images were collected from real paddy fields using a high-resolution (1,080 x 1,440 pixels) smartphone camera. The collected images were carefully cleaned and annotated with the help of an agronomist.

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The Research Paper "Detection of Bicep Form Using Myoware and Machine Learning" based on the novel dataset has been recently accepted in September 2022 and is being published in SCOPUS Indexed SPRINGER Book Series “Lecture Notes in Networks and Systems”

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