1. Correction: Yuldashev et al. Parking Lot Occupancy Detection with Improved MobileNetV3. Sensors 2023, 23 , 7642.
- Author
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Yuldashev, Yusufbek, Mukhiddinov, Mukhriddin, Abdusalomov, Akmalbek Bobomirzaevich, Nasimov, Rashid, and Cho, Jinsoo
- Subjects
ARTIFICIAL neural networks ,PATTERN recognition systems ,SMART parking systems ,CONVOLUTIONAL neural networks ,OBJECT recognition (Computer vision) ,DEEP learning ,HOUGH transforms - Abstract
This document is a correction notice for an article titled "Parking Lot Occupancy Detection with Improved MobileNetV3" published in the journal Sensors. The correction includes errors in figures and figure legends, as well as text corrections in various sections of the article. The article discusses different approaches to parking lot occupancy detection, including traditional machine learning approaches and deep learning approaches. It also mentions several studies that have proposed methods using feature extraction and machine learning methodologies. The article compares different deep neural networks and datasets used for parking occupancy classification. The correction notice provides updated figures and corrects errors in the text. This document is a correction to a previous article. It provides a revised list of references for the article, ensuring that the correct sources are cited. The correction does not affect the scientific conclusions of the original article. The document also includes three figures: Figure 6 shows a graph of empty and busy parking spaces, Figure 7 displays samples from the CNRPark-EXT dataset taken in different weather conditions, and Figure 8 shows examples of different parking lots and weather conditions from the PKLot dataset. The authors of the correction are Yusufbek Yuldashev, Mukhriddin Mukhiddinov, Akmalbek Bobomirzaevich Abdusalomov, Rashid Nasimov, and Jinsoo Cho. [Extracted from the article]
- Published
- 2024
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