Deep learning for decentralized parking lot occupancy detection
By Giuseppe Amato, Fabio Carrara, Fabrizio Falchi, Claudio Gennaro, C. Meghini, Claudio Vairo. 2017
341 citations recorded by the source corpus.
Subfields: Building and Construction, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Building and Construction
- Ala Al-Fuqaha
- M. Mohammadi
- Luca Ciampi
- Giuseppe Amato
- Claudio Gennaro
- Mohsen Guizani
- Sameh Sorour
- Ekram Hossain
In Computer Vision and Pattern Recognition
- Luca Ciampi
- Giuseppe Amato
- Claudio Gennaro
- Fabrizio Falchi
- Fotios Zantalis
- Ala Al-Fuqaha
- Mohsen Guizani
- Sameh Sorour
In Electrical and Electronic Engineering
- Ala Al-Fuqaha
- M. Mohammadi
- Luca Ciampi
- Giuseppe Amato
- Claudio Gennaro
- Mohsen Guizani
- Sameh Sorour
- Fabrizio Falchi
Citations in the corpus
- Deep Learning for IoT Big Data and Streaming Analytics: A Survey (2017, methodology): “[119] developed a decentralized system to identify the occupied and empty spots in parking lots using smart cameras and deep CNNs.”
- Counting Vehicles with Cameras (2018, methodology): “Comparisons with the state of the art We have compared our vehicles counting solution against the method proposed in [2], a state-of-the-art approach for car parking occupancy detection, based on mAlexNet, a deep CNN specifically designed for smart cameras.”
- A Review of Machine Learning and IoT in Smart Transportation (2019, methodology): “The authors in [20], use CNNs on data obtained from smart cameras on parking lots, to detect free parking slots.”
- Explainable Artificial Intelligence Applications in Cyber Security: State-of-the-Art in Research (2022, background): “[135] CNRPark+EXT 2017 282 The CNRPark+EXT dataset, which was created on a parking lot with 164 spaces, has around 150,000 annotated pictures (patches) of vacant and occupied parking places.”
- Counting Vehicles with Deep Learning in Onboard UAV Imagery (2019, methodology): “Prior methods able to perform onboard computations, like [12], assume that the”
- A Survey of Deep Learning and Its Applications: A New Paradigm to Machine Learning (2019, background): “For detecting parking lot occupation, Amato et al. [5] proposed a new decentralized solution for the classification of images of a parking space when occupied directly on the smart cameras.”