A dataset of QR Codes on top of different surfaces (flat and challenging surfaces)

This comprehensive dataset consists of a diverse collection of images, primarily focusing on QR codes placed on different surfaces. The dataset is meticulously organized into three main categories: "flat," "random," and "synthetic_small."The "flat" category encompasses images of QR codes positioned exclusively on planar surfaces, providing a foundational dataset for various computer vision tasks. In contrast, the "random" category presents a more challenging dataset, featuring QR codes placed on surfaces with varying orientations and complexities. Lastly, the "synthetic_small" category focuses on synthetic images with QR codes on planar surfaces, enhancing the dataset's depth and applicability.Annotations for the dataset are meticulously provided in JSON format, furnishing essential metadata for each image. These annotations are invaluable for tasks such as image classification, analysis, and, notably, object detection of QR codes.With its wide-ranging content and meticulously structured data, this dataset serves as a vital resource for researchers and practitioners in the field of computer vision. It enables exploration and development of algorithms across various domains, offering a diverse set of challenges and opportunities for advancing computer vision capabilities in the context of QR code recognition on different surfaces.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

A dataset of color QR Codes generated using back-compatible and random colorization algorithms exposed to different illumination-capture channel conditions

Color QR Codes are often generated to encode digital information, but one also could use colors or to allocate colors in a QR Code to act as a color calibration chart. In this dataset, we present several thousand QR Codes images generated with two different colorization algorithms (random and back-compatible) and several tuning variables in these color encoding. The QR Codes were also exposed to three different channel conditions (empty, augmentation and real-life). Also, we derive the SNR and BER computations for these QR Code in comparison with their black and white versions. Finally, we also show if ZBar, a commercial QR Code scanner, is able to read them.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

How to implement a selective colorimetric gas sensor with off the shelf components?

We report on how an inexpensive and very selective gas sensor can be implemented, simply combining colorimetric indicators casted on top of Scotch® tape, with a commercial microchip adapted here to measure optical reflectance. The system can be easily reproduced (leading to quantitatively consistent results), refreshed and reconfigured to sense different target gases, just replacing the colorimetric

Colorimetric sensor for bad odor detection using automated color correction

Colorimetric sensors based on color-changing dyes offer a convenient approach for the quantitative measurement of gases. An integrated, mobile colorimetric sensor can be particularly helpful for occasional gas measurements, such as informal air quality checks for bad odors. In these situations, the main requirement is high availability, easy usage, and high specificity towards one single chemical compound, combined with cost-efficient production. In this contribution, we show how a well stablished colorimetric method can be adapted for easy operation and readout, making it suitable for the untrained end user. As an example, we present the use of pH indicators for the selective and reversible detection of NH3 in air (one relevant gas contributing to bad odors) using gas-sensitive layers dip coated on glass substrates. Our results show that the method can be adapted to detect NH3 concentrations lower than 1 ppm, with measure-to-result times in the range of a few minutes. We demonstrate that the color measurements can be carried out with the optical signals of RGB sensors, without losing quantitative performance

Stress neuropeptide levels in adults with chest pain due to coronary artery disease: potential implications for clinical assessment

: Substance P (SP) and neuropeptide Y (NPY) are neuropeptides involved in nociception. The study of biochemical markers of pain in communicating critically ill coronary patients may provide insight for pain assessment and management in critical care. Purpose of the study was to to explore potential associations between plasma neuropeptide levels and reported pain intensity in coronary critical care adults, in order to test the reliability of SP measurements for objective pain assessment in critical care