Extracting the boundaries of Photovoltaic (PV) plants is essential in the process of aerial inspection and autonomous monitoring by aerial robots. This method provides a clear delineation of the utility-scale PV plants’ boundaries for PV developers, Operation and Maintenance (O&M) service providers for use in aerial photogrammetry, flight mapping, and path planning during the autonomous monitoring of PV plants. 

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497 Views

Detection results of the CircleNet with all test dataset with 1826 images

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50 Views

The study of mouse social behaviours has been increasingly undertaken in neuroscience research. However, automated quantification of mouse behaviours from the videos of interacting mice is still a challenging problem, where object tracking plays a key role in locating mice in their living spaces. Artificial markers are often applied for multiple mice tracking, which are intrusive and consequently interfere with the movements of mice in a dynamic environment.

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A custom made multispectral camera was used to collect a novel dataset of images of untreated lettuce leaves or leaves treated with vinegar, oil, or a combination of these. The camera captured image data at 10 wavelengths ∈[380nm,980nm] across the electromagnetic spectrum in the visible and NIR (near-infrared) regions. Imaging was done in a lab environment with the presence of ambient light.

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This dataset is a collection of images and their respective labels containing examples of multiple Brazilian coins, the primary purpose is to support the development of Computer Vision techniques for automatic detection of such objects, i.e., localization and classification tasks. 

Instructions: 

The dataset is divided in classification and regression, where the classification set contains 3056 images with a single coin and its respective annotation file, the regression set contains all the images from the classification set and other images with several coins and labels, amounting to 6021 images.

 

This dataset provides two annotations formats, the labelme and COCO format;

The labelme format consists of one json per image, where the labels can assume one of two types: circle or polygon; A circle label has a center and edge point, and a polygon is a set of points (Polygons where used for partial coins). 

The COCO format, consists of a single json for the dataset.

Scripts for visualization are provided for both formats.

 

Further information about the formats can be found on the following links:

http://cocodataset.org/#home

https://github.com/wkentaro/labelme

 

Acknowledgments:

Moneda thanks Luciana Harada and Rafael de Souza, his group in the college course that generated these datasets. Yonekura and Guedes acknowledge the grant PPP 04/2017 provided by FAPEAM/CNPq and the label review carried out by Natan Siqueira.

 

 

 

 

 

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453 Views

This dataset is used for arbitrary-orientation scene text detection, recognition and spotting.

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54 Views

Dataset of rosbags collected during autonomous drone flight inside a warehouse of stockpiles. PCD files created using reconstruction method proposed by article.

Data still being move to IEEE-dataport. 

Instructions: 

Bag files contais multiple topics. Proposed method uses mainly Velodyne lidar pointcloud information and DJI imu

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350 Views

  

About

Dataset described in: 

Daudt, R.C., Le Saux, B., Boulch, A. and Gousseau, Y., 2019. Multitask learning for large-scale semantic change detection. Computer Vision and Image Understanding, 187, p.102783.

 

This dataset contains 291 coregistered image pairs of RGB aerial images from IGS's BD ORTHO database. Pixel-level change and land cover annotations are provided, generated by rasterizing Urban Atlas 2006, Urban Atlas 2012, and Urban Atlas Change 2006-2012 maps. 

 

The dataset is split into five parts:

    - 2006 images 

Instructions: 

 

Please contact us if you have any questions.

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5535 Views

Master data has played a significant role in improving operational efficiencies and has attracted the attention of many large businesses over the decade. Recent professional searches have also proved a significant growth in the practice and research of managing these master data assets.

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163 Views

Pressing demand of workload along with social media interaction leads to diminished alertness during work hours. Researchers attempted to measure alertness level from various cues like EEG, EOG, Video-based eye movement analysis, etc. Among these, video-based eyelid and iris motion tracking gained much attention in recent years. However, most of these implementations are tested on video data of subjects without spectacles. These videos do not pose a challenge for eye detection and tracking.

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373 Views

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