Predicting crime using deep learning

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.

Opis bibliograficzny
Główni autorzy:	Shihab, Muhammad Nafees, Chowdhury, Anupam, Mahmood, SK. Belayet
Kolejni autorzy:	Chakrabarty, Amitabha
Format:	Praca dyplomowa
Język:	English
Wydane:	Brac University 2024
Hasła przedmiotowe:	Deep learning Criminal incident Supervised classification LSTM CNN Shallow dense model Deep learning (Machine learning)
Dostęp online:	http://hdl.handle.net/10361/23963

id	10361-23963
record_format	dspace
spelling	10361-239632024-09-03T21:01:16Z Predicting crime using deep learning Shihab, Muhammad Nafees Chowdhury, Anupam Mahmood, SK. Belayet Chakrabarty, Amitabha Khan, Rubayat Ahmed Department of Computer Science and Engineering, Brac University Deep learning Criminal incident Supervised classification LSTM CNN Shallow dense model Deep learning (Machine learning) This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017. Cataloged from PDF version of thesis. Includes bibliographical references (pages 47-52). Criminal activities are available in every region of the world influencing social life and financial improvement. As such, it is a major concern of numerous legislatures who are utilizing distinctive advanced innovation to handle such issues. Crime Analysis, a sub branch of criminology, considers the behavioral example of criminal activities and tries to recognize the pointers of such events. Distinguishing the patterns of criminal activity of a place is vital in order to prevent it. Law enforcement organizations can work effectively and respond more rapidly if they have better knowledge about crime patterns in different geological points of a city. Deep learning agents work with data and utilize distinctive systems to discover patterns in data making it exceptionally helpful for predictive analysis. Law enforcement agencies utilize diverse patrolling techniques in light of the data they get the chance to keep a region secure. The aim of this paper is to use deep learning models to predict and classify a criminal incident by type, depending on its occurrence at a given location. The experimentation is conducted on a dataset containing crime records. For this supervised classification problem, we used a new approach - LSTM (Long Short Term Memory) and was able to classify crimes with 64.2% accuracy. CNN (Convolutional Neural Network) & Shallow dense model were used also. Solving the imbalanced class problem, the deep learning agent was able to classify crimes. Muhammad Nafees Shihab Anupam Chowdhury SK. Belayet Mahmood B.Sc. in Computer Science and Engineering 2024-09-03T12:19:26Z 2024-09-03T12:19:26Z 2017 2017-12-24 Thesis ID: 13301097 ID: 13301091 ID: 13301100 http://hdl.handle.net/10361/23963 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 52 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Deep learning Criminal incident Supervised classification LSTM CNN Shallow dense model Deep learning (Machine learning)
spellingShingle	Deep learning Criminal incident Supervised classification LSTM CNN Shallow dense model Deep learning (Machine learning) Shihab, Muhammad Nafees Chowdhury, Anupam Mahmood, SK. Belayet Predicting crime using deep learning
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.
author2	Chakrabarty, Amitabha
author_facet	Chakrabarty, Amitabha Shihab, Muhammad Nafees Chowdhury, Anupam Mahmood, SK. Belayet
format	Thesis
author	Shihab, Muhammad Nafees Chowdhury, Anupam Mahmood, SK. Belayet
author_sort	Shihab, Muhammad Nafees
title	Predicting crime using deep learning
title_short	Predicting crime using deep learning
title_full	Predicting crime using deep learning
title_fullStr	Predicting crime using deep learning
title_full_unstemmed	Predicting crime using deep learning
title_sort	predicting crime using deep learning
publisher	Brac University
publishDate	2024
url	http://hdl.handle.net/10361/23963
work_keys_str_mv	AT shihabmuhammadnafees predictingcrimeusingdeeplearning AT chowdhuryanupam predictingcrimeusingdeeplearning AT mahmoodskbelayet predictingcrimeusingdeeplearning
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Predicting crime using deep learning

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