Types of Car Detection by using Deep Learning Algorithms

Project Code :TCMAPY1011

Objective

To develop and evaluate the performance of deep learning algorithms for accurate car detection in various scenarios and conditions, thereby assisting in improved traffic monitoring, autonomous navigation, and enhanced safety protocols

Abstract

Deep Learning (DL), a subset of AI, has changed various spaces, one of which is the car business. In particular, vehicle identification in pictures and recordings has seen huge headways because of the reception of DL calculations. The primary deep learning-based car detection methods are examined in this paper. The convolutional brain organization (CNN) stands apart as an essential engineering utilized for vehicle discovery undertakings. Since these networks automatically learn feature spatial hierarchies from raw data, they are extremely effective at recognizing intricate vehicle patterns, shapes, and textures in a variety of environments.

Keywords: car dataset, deep learning algorithms etc...

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

H/W CONFIGURATION:

Processor - I3/Intel Processor

Hard Disk - 160GB

Key Board - Standard Windows Keyboard

Mouse - Two or Three Button Mouse

Monitor - SVGA

RAM - 8GB


S/W CONFIGURATION:

β€’ Operating System :  Windows 7/8/10

β€’ Server side Script :  HTML, CSS, Bootstrap & JS

β€’ Programming Language :  Python

β€’ Libraries :  Flask, Pandas

β€’ IDE/Workbench :  PyCharm


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