Overview of Image Datasets for Deep Learning Applications in Diagnostics of Power Infrastructure.

The power sector is one of the most important engineering sectors, with a lot of equipment that needs to be appropriately maintained, often spread over large areas. With the recent advances in deep learning techniques, many applications can be developed that could be used to automate the power line inspection process, replacing previously manual activities. However, in addition to these novel algorithms, this approach requires specialized datasets, collections that have been properly curated and labeled with the help of experts in the field.

Early detection of Solanum lycopersicum diseases from temporally-aggregated hyperspectral measurements using machine learning.

Some plant diseases can significantly reduce harvest, but their early detection in cultivation may prevent those consequential losses. Conventional methods of diagnosing plant diseases are based on visual observation of crops, but the symptoms of various diseases may be similar. It increases the difficulty of this task even for an experienced farmer and requires detailed examination based on invasive methods conducted in laboratory settings by qualified personnel.

Soil Moisture a Posteriori Measurements Enhancement Using Ensemble Learning.

This work aimed to assess the recalibration and accurate characterization of commonly used smart soil-moisture sensors using computational methods. The paper describes an ensemble learning algorithm that boosts the performance of potato root moisture estimation and increases the simple moisture sensors' performance. It was prepared using several month-long everyday actual outdoor data and validated on the separated part of that dataset.

Deep potato - The hyperspectral imagery of potato cultivation with reference agronomic measurements dataset: Towards potato physiological features modeling.

The datasets provide hyperspectral imagery of potato fields with referencing agronomic measurements of several parameters. It contains also meteorological data collected on the place at the same time and some additional data on the variety of potatoes and the experiment. The experiment has been conducted in 2020 and two different potato varieties (Lady Claire and Markies) on the different soil profiles were planted and observed.

The collection of images of an insulator taken outdoors in varying lighting conditions with additional laser spots.

Electrical insulators are elements of power lines that require periodical diagnostics. Due to their location on the components of high-voltage power lines, their imaging can be cumbersome and time-consuming, especially under varying lighting conditions. Insulator diagnostics with the use of visual methods may require localizing insulators in the scene.