Parking detection plays a pivotal role in the development of smart cities, aiding in the
efficient management of urban parking spaces. With the advent of edge computing, devices …

In this paper, we present an object detection based algorithm to automatically map the
parking spaces in a parking lot, instead of manually mapping them. The work addresses an …

Parking space detection is a major challenge in our cities and drivers waste time when
moving from one place to another in search of a free parking space. The current parking …

Finding parking spaces is a time-consuming and fuel-wasting task, especially in crowded
areas. To address this issue, researchers have proposed an automatic parking detection …

This paper proposes a unique real-time street parking detection scheme that utilizes visual
information and the YOLOv4 convolutional neural network to accurately detect available …

Object detection is central to computer vision, drawing significant attention lately. Deep
learning techniques shine for their precision, robustness, and speed. Their integration into …

In this paper, we present a Faster R-CNN based object detection scheme to automatically
map the parking spaces in a parking lot, instead of manually mapping them. The work …

In the face of escalating urbanization and its associated parking challenges, this paper
proposes an innovative approach to enhance parking lot management and optimize space …

Parking congestion presents a significant challenge in urban areas worldwide, spanning
both developed and developing nations. The escalating volume of vehicles compounds the …

To solve real-life problems for different smart city applications, using deep Neural Network,
such as parking occupancy detection, requires fine-tuning of these networks. For large …