Image Processing
Please cite the following paper when using this dataset:
N. Thakur, "Twitter Big Data as a Resource for Exoskeleton Research: A Large-Scale Dataset of about 140,000 Tweets from 2017–2022 and 100 Research Questions", Journal of Analytics, Volume 1, Issue 2, 2022, pp. 72-97, DOI: https://doi.org/10.3390/analytics1020007
Abstract
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In recent years, many unmanned retail stores have been introduced with the development
of computer vision, sensors and wireless technology. However, the trend has slowed due to the costs
associated with implementation. A vision-based kiosk, which is only equipped with a vision sensor, can
be a compact and affordable option. The vision-based kiosk detects a product via CNN-based object
detectors and performs instance-level classification by aggregating detections from multiple cameras.
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Computer vision and image processing have made significant progress in many real-world applications, including environmental monitoring and protection. Recent studies have shown that computer vision and image processing can be used to quantify water turbidity, a crucial physical parameter in water quality assessment. This paper presents a procedure to determine water turbidity using deep learning methods, specifically, convolutional neural network (CNN). At first, water samples were located inside a dark cabin before digital images of the samples were captured with a smartphone camera.
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Here, a dataset used in manuscript "Wide-Area Land Cover Mapping with Sentinel-1 Imagery using Deep Learning Semantic Segmentation Models" Scepanovic et al. (https://doi.org/10.1109/JSTARS.2021.3116094) is published. The data contains preprocessed SAR backscatter digital numbers as 7000 geotiff image patches of size 512x512 (about 10 km x 10 km size) sampled from several wide-area SAR mosaics compiled from all summer Sentinel-1A images acquired over Finland in the summer of 2018.
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ABSTRACT
Europe is covered by distinct climatic zones which include semiarid, the Mediterranean, humid subtropical, marine,
humid continental, subarctic, and highland climates. Land use and land cover change have been well documented in the
past 200 years across Europe1where land cover grassland and cropland together make up 39%2. In recent years, the
agricultural sector has been affected by abnormal weather events. Climate change will continue to change weather
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MATLAB code for the proposed Single-shot Super-Resolution Phase Retrieval (SSR-PR) algorithm.
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The iSAID-Reduce100 is a reduced version of the DOTA dataset for instance segmentation task, including 1400 training samples and 1362 validation samples. The images are captured from multiple sensors and cropped to (512, 512).
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