Using deep learning algorithms to detect violent activities
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2019.
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BRAC University
2019
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| Acesso em linha: | http://hdl.handle.net/10361/12270 |
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10361-122702022-01-26T10:20:09Z Using deep learning algorithms to detect violent activities Ammar, S.M. Rojin Anjum, Md. Tanvir Rounak Islam, Md. Touhidul Islam Alam, Md. Ashraful Department of Computer Science and Engineering, Brac University Machine learning Violence detection Neural network DarkNet-19 Machine learning. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2019. Cataloged from PDF version of thesis. Includes bibliographical references (pages 35-40). It is of extensive importance to develop a technique for automatic surveillance video analysis to recognize the presence of violence. In this work, to identify violent videos, we put forward a deep neural network. For extracting frame level features from a video, a convolutional neural network is used with a pre-trained ImageNet model. The characteristics of the frame level are then aggregated using a long short-term memory variant that uses fully connected layers and leaky recti ed linear units. Together with the long short-term memory, the convolutional neural network is capable of capturing localized spatio-temporal features that enable the analysis of local motion in the video. The performance is further evaluated in terms of accuracy of recognition on three standard benchmark datasets. In order to determine the capabilities of our proposed model, we also compared our system results with other techniques. The approach proposed outperforms state-of - the-art methods while processing the videos in real time. S.M. Rojin Ammar Md. Tanvir Rounak Anjum Md. Touhidul Islam B. Computer Science and Engineering 2019-06-30T03:46:35Z 2019-06-30T03:46:35Z 2019 2019-05 Thesis ID 15101026 ID 16301140 ID 15301133 http://hdl.handle.net/10361/12270 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. 40 pages application/pdf BRAC University |
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Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Machine learning Violence detection Neural network DarkNet-19 Machine learning. |
| spellingShingle |
Machine learning Violence detection Neural network DarkNet-19 Machine learning. Ammar, S.M. Rojin Anjum, Md. Tanvir Rounak Islam, Md. Touhidul Islam Using deep learning algorithms to detect violent activities |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2019. |
| author2 |
Alam, Md. Ashraful |
| author_facet |
Alam, Md. Ashraful Ammar, S.M. Rojin Anjum, Md. Tanvir Rounak Islam, Md. Touhidul Islam |
| format |
Thesis |
| author |
Ammar, S.M. Rojin Anjum, Md. Tanvir Rounak Islam, Md. Touhidul Islam |
| author_sort |
Ammar, S.M. Rojin |
| title |
Using deep learning algorithms to detect violent activities |
| title_short |
Using deep learning algorithms to detect violent activities |
| title_full |
Using deep learning algorithms to detect violent activities |
| title_fullStr |
Using deep learning algorithms to detect violent activities |
| title_full_unstemmed |
Using deep learning algorithms to detect violent activities |
| title_sort |
using deep learning algorithms to detect violent activities |
| publisher |
BRAC University |
| publishDate |
2019 |
| url |
http://hdl.handle.net/10361/12270 |
| work_keys_str_mv |
AT ammarsmrojin usingdeeplearningalgorithmstodetectviolentactivities AT anjummdtanvirrounak usingdeeplearningalgorithmstodetectviolentactivities AT islammdtouhidulislam usingdeeplearningalgorithmstodetectviolentactivities |
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1814309278764236800 |