Image recognition by deep learning
Includes bibliographical references (pages 33-34).
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BRAC University
2018
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| Online Erişim: | http://hdl.handle.net/10361/9022 |
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10361-90222022-01-26T10:15:52Z Image recognition by deep learning Mohiuddin, Karishma Das, Amit Kishor Obaid, Habiba Bint Ali, Md. Haider Uddin, Dr. Jia Department of Computer Science and Engineering, BRAC University Image recognition Deep learning Object recognition CNN method HAAR Cascade Classifier Includes bibliographical references (pages 33-34). This thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017. Object recognition has become a crucial topic in the field of computer vision. Poor qualities of images unable bring out the desired object as per expectancy. Many models have proposed to recognize object from image. However, most of these approaches hardly achieve high accuracy and precision. It creates a major obstacle to get correctness of the research because of the lighting, illumination, image quality, noise, ethnicity and various angels of similar objects. Therefore, we have proposed a novel approach to detect any object by CNN method including HAAR Cascade classifier where we first detect the most prominent features from scene using Haar Feature Based Cascade Classifier that has been introduced by Paul Viola and Michael Jones. In the second phase, the classification has been used for Convolutional Neural Network to detect the object automatically with better accuracy and more efficiently. It can determine any object after proper training and dataset manipulation. Our proposed method for image recognition has achieved very good accuracy than our expectation. Karishma Mohiuddin Amit Kishor Das Habiba Bint Obaid B. Computer Science and Engineering 2018-01-11T06:18:31Z 2018-01-11T06:18:31Z 2017 8/21/2017 Thesis ID 13101137 ID 13301096 ID 13301026 http://hdl.handle.net/10361/9022 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. 34 pages application/pdf BRAC University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Image recognition Deep learning Object recognition CNN method HAAR Cascade Classifier |
| spellingShingle |
Image recognition Deep learning Object recognition CNN method HAAR Cascade Classifier Mohiuddin, Karishma Das, Amit Kishor Obaid, Habiba Bint Image recognition by deep learning |
| description |
Includes bibliographical references (pages 33-34). |
| author2 |
Ali, Md. Haider |
| author_facet |
Ali, Md. Haider Mohiuddin, Karishma Das, Amit Kishor Obaid, Habiba Bint |
| format |
Thesis |
| author |
Mohiuddin, Karishma Das, Amit Kishor Obaid, Habiba Bint |
| author_sort |
Mohiuddin, Karishma |
| title |
Image recognition by deep learning |
| title_short |
Image recognition by deep learning |
| title_full |
Image recognition by deep learning |
| title_fullStr |
Image recognition by deep learning |
| title_full_unstemmed |
Image recognition by deep learning |
| title_sort |
image recognition by deep learning |
| publisher |
BRAC University |
| publishDate |
2018 |
| url |
http://hdl.handle.net/10361/9022 |
| work_keys_str_mv |
AT mohiuddinkarishma imagerecognitionbydeeplearning AT dasamitkishor imagerecognitionbydeeplearning AT obaidhabibabint imagerecognitionbydeeplearning |
| _version_ |
1814308446797824000 |