My Account | Careers | Downloads | Blog

PROJECT TITLE :

Vehicles Detection for Smart Roads Applications on Board of Smart Cameras A Comparative Analysis

ABSTRACT:

The use of video analytics in smart roads environments can be lucratively adopted for the purpose of automatically detecting abnormal circumstances. In this context, the first and most important stage is vehicle detection, and it is essential that this stage be accurate because any mistake in vehicle detection will affect the performance of any step that comes after it. Additionally, in smart road environments, it is frequently preferred to perform the video analysis directly on board of smart surveillance cameras. This is done in order to decrease bandwidth usage and eliminate the cost of setting up and maintaining powerful processing servers. On the other hand, processing on board of smart cameras implies that the detection algorithm must be quick and slim because the resources available on this kind of embedded device are limited. In this day and age of Deep Learning, it would appear that the question of which method is the most effective one for detecting vehicles may have an easy answer, given that this category of methods includes some that are exceptionally precise. In any case, according to the considerations presented above, the method that is best suited for this application is not necessarily the most accurate one, but it is without a doubt the most accurate one that can run on the hardware that is currently available at a particular frame rate and resolution. In this paper, we perform an analysis of the methods available in the literature for vehicle detection, by comparing them in terms of accuracy and computational burden, with the aim of answering the following question: what is the best method for vehicles detection when working with smart cameras? Starting from the considerations presented above, we perform this analysis in order to answer the question.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Short Text Topic Modeling Techniques, Applications, and Performance: A Survey ABSTRACT: The semantic understanding of short texts is required for a wide variety of real-world applications, so their analysis allows
PROJECT TITLE : Deep Generative Modelling A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models ABSTRACT: Deep generative models are a category of methods that train deep neural networks
PROJECT TITLE : Attention in Reasoning Dataset, Analysis, and Modeling ABSTRACT: Although attention has become an increasingly popular component in deep neural networks for the purpose of both interpreting data and improving
PROJECT TITLE : Comparative Analysis of Decentralized Identity Approaches ABSTRACT: When trust and performance cannot be placed in the hands of a single organization, decentralization is an absolute necessity. Examples of Distributed
PROJECT TITLE :Cost-Optimal Caching for D2D Networks With User Mobility: Modeling, Analysis, and Computational Approaches - 2018ABSTRACT:Caching well-liked files at the user equipments (UEs) provides an efficient way to alleviate

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry