Digitalization of Microscopic Images of Polymers and Composite Materials from the Central Research Institute of Polymers and Artificial Leathers (SEM, TEM, optical plastolgraphy / polymerography).

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Digitalization of Microscopic Images of Polymers and Composite Materials from the Central Research Institute of Polymers and Artificial Leathers (SEM, TEM, optical plastolgraphy / polymerography).

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Digitalization of Microscopic Images of Polymers and Composite Materials from the Central Research Institute of Polymers and Artificial Leathers (SEM, TEM, optical plastolgraphy / polymerography).

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The data contains both CST data and Experiment data which used at the paper:'Validation of a three-dimensional DBIM-TwIST algorithm for microwave tomography'.

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The date fruit dataset was created to address the requirements of many applications in the pre-harvesting and harvesting stages. The two most important applications are automatic harvesting and visual yield estimation. The dataset is divided into two subsets and each of them is oriented into one of these two applications. The first dataset consists of 8079 images of more than 350 date bunches captured from 29 date palms. The date bunches belong to five date types: Naboot Saif, Khalas, Barhi, Meneifi, and Sullaj.

Instructions: 

Please refer to the readme and documentation files for a full description.

The complete documentation of the dataset is available in the following article:

https://doi.org/10.1016/j.dib.2019.104514

Some experiments were performed on the dataset-1 and the results can be found in the following article:  [To download the dataset-1 as processed and categorized in this article, refer to the zip file named "DATASET-1 (224 X 224) Categorized.zip"]

https://doi.org/10.1109/ACCESS.2019.2936536

You can visit our website for more details and related resources:

https://sites.google.com/view/daterobotic/home

 

This data is divided into two sets. 

DATASET-1 consists of 8079 images of date bunches that were taken using two color cameras from different angles and scales during one season in six imaging sessions (recording times) over the period of Jun-Sep 2016. The date bunches belong to five date varieties: Naboot Saif, Khalas, Barhi, Meneifi, and Sullaj. 

DATASET-1 zip files:

---- DATASET-1.zip (42 GB)

     High resolution images (8079 images) 

---- DATASET-1_(224 X 224).zip (108 MB)

     A preview of the 8079 images. Images size: 224 X 224.

---- DATASET-1 (224 X 224) Categorized.zip (649 MB)

     This file contains the images of dataset-1 resized to 224x224 pixels and categorized into subfolders according to date fruit type, maturity state, and the harvesting decision. This categorization, and image resolution, is related to the experiments described in ref [2].

---- DATASET-1_(annotation files).zip (104 KB)

     The annotation (labeling) files for type classification, maturity analysis, and harvesting decision applications. The labeling instructions and rules are explained in detail in Ref. [2].

  

DATASET-2 contains images, videos, and weight measurements that were acquired during the harvesting period of Barhi dates.

DATASET-2 files:

---- DATASET-2_images_Barhi_date_bunches_on_orchard.zip (16.44 GB)

     Images of 152 Barhi date bunches before and during harvesting.

---- DATASET-2_images_Barhi_date_bunches_front_graph_paper.zip (88.16 MB)

     Images of the 152 Barhi date bunches in front of graph paper.

---- DATASET-2_weight_measurements_Barhi_date_bunches.xlsx (683.99 KB)

     The weight measurements of the 152 Barhi date bunches.

---- DATASET-2_videos_Barhi_date_palms.zip (4.49 GB)

     360-degree videos of the nine Barhi date palms (120 date bunches).

---- DATASET-2_images&measurements_Sullaj_date_bunches_front_graph_paper.zip (76 MB)

     Images of 11 Sullaj date bunches in front of graph paper with weight & dimensions measurements.

---- DATASET-2_images&measurements_individual_dates&bunches_stalks.zip (549.18 MB)

     Images of individual dates and bunches' stalks with weight & dimensions measurements.

  

 

 

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Occlusion, glare and secondary reflections formed due to and on the spectacles - results in poor detection, localization, and recognition of eye/face features. We term all the problems related to the usage of spectacles as The spectacle problem. Though several studies on the spectacle detection and removal have been reported in the literature, the study focusing on spectacle problem removal is very limited. One of the main reasons being, the nonavailability of a facial image database highlighting the spectacle problems.

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