Image Processing

We created a 2563-image custom dragon fruit image dataset, with 1248 images of raw dragon fruits and 1315 photographs of ripe dragon fruits. The images were taken with the Nikon D5200 DSLR and OnePlus 6's Sony IMX 519 16 megapixel camera. The photographs taken with the DSLR camera had a resolution of 4000 by 6000 pixels, while those taken with the OnePlus6 had a resolution of 3456 by 4608 pixels. They were photographed in natural sunlight. The average temperature during that time was 28°C (84.2°F), with partly sunny skies, 65 percent humidity, and 17 km/h wind speeds.

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This dataset has a collection of 383 raw images of Indian vehicles in different illumination conditions using Infrared Day/Night Camera. The dataset resembles the Indian highway toll collection plazas. The dataset will be useful in developing intelligent models for applications such as automated toll collection, number plate detection and recognition, driverless vehicles, suspicious vehicle traction, and traffic management.

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Two in-air signature databases were created. Forty participants voluntarily took part in each of the two databases’ construction. Some of them participated in both databases construction. Each participant signs in the air five signatures and imitates five signatures of five other participants.

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Abstract

This synthetic dataset or phantom consists of 6 raw format databases, in the three–dimensional (3-D) domain, which are identified as follows:

DB1: Ground Truth

DB2: Poisson noise

DB3: Stair-step artifact

DB4: Streak artifact

DB5: Both artifacts

DB6: Hybrid.

 

 

 

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This is a dataset about clustered pop-pepper in Guiyang, China. Some of our depth data are distorted, but generally available. It will be continuously updated in the future.

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Dataset for segmentation of the defects on the surfaces of the military cartridge cases. The datasets with non-defective, defective and masked image classes of the defective cartridge cases.

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This open dataset is subject to CC BY-NC-SA 4.0 License. The dataset is intended for scientific research purposes and it cannot be used for commercial purposes. The authors encourage users to use it for public research and as a testbench for private research. Please note that any promotional/marketing material built upon this dataset should be backed by publicly available description of the work leading to the promotional/marketing claims.

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The dataset contains results of the paper being submitted.

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This repository contains code to apply the ESPER method to quasi-continuum models of biomolecules exhibiting multiple degrees of freedom, as described in Seitz et al. (2022, IEEE TCI). As inputs into ESPER, detailed instructions are also provided for generating custom synthetic datasets with increasing complexity to mirror known cryo-EM image attributes.

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Currency recognition and classification is one essential task to do. Both paper and coin currency play important role in transactions in everyday life. But provided there are many datasets available of paper currency, and very less datasets are available of coin currency.  Coin currency recognition becomes important because even though the amount for which people do coin transactions is small but inaccuracy in recognition can lead to huge loss. Following are the objectives to create this dataset:

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