Extracting book titles from book recommendation videos using a deep learning approach

Bartu Sarımehmetoğlu; Hamit Erdem

Article Details

Extracting book titles from book recommendation videos using a deep learning approach

Authors:

Bartu Sarımehmetoğlu | Hamit Erdem

Publisher:

Kyrgyz-Turkish Manas University

Main Topics:

Electrical Engineering (Other)

Journal:

MANAS Journal of Engineering Vol.11 Issue 2, pp.229-234

Document Type:

Article

Publication Date:

12/2023

Document Language:

English

Document ID (Org No.):

2001306604

pISSN:

1694-7398

Keywords:

Abstract:

 Extracting text from images and videos is an emerging field of research with a wide range of applications, including video search, video editing, and translation. Nowadays, book promotion videos in different languages are shared on social media and especially on YouTube. In this study; It is recommended to take book titles through book promotion videos. The developed system takes video as input and separates the names of the books. The viewer can select the desired book by clicking on the detected book titles and watch the relevant part of the video. This application result in time saving by the viewer. In order to achieve this application, a deep learning-based system was developed to retrieve the names of books from videos. YOLO-based method was used in the study. Different YOLO algorithms were used in the study, and YOLOv5 was found to be more successful. This study contributes to the field of text extraction and video analysis by developing a deep learning-based approach to extract book titles from book promotion videos.

 Extracting text from images and videos is an emerging field of research with a wide range of applications, including video search, video editing, and translation. Nowadays, book promotion videos in different languages are shared on social media and especially on YouTube. In this study; It is recommended to take book titles through book promotion videos. The developed system takes video as input and separates the names of the books. The viewer can select the desired book by clicking on the detected book titles and watch the relevant part of the video. This application result in time saving by the viewer. In order to achieve this application, a deep learning-based system was developed to retrieve the names of books from videos. YOLO-based method was used in the study. Different YOLO algorithms were used in the study, and YOLOv5 was found to be more successful. This study contributes to the field of text extraction and video analysis by developing a deep learning-based approach to extract book titles from book promotion videos.

 Extracting text from images and videos is an emerging field of research with a wide range of applications, including video search, video editing, and translation. Nowadays, book promotion videos in different languages are shared on social media and especially on YouTube. In this study; It is recommended to take book titles through book promotion videos. The developed system takes video as input and separates the names of the books. The viewer can select the desired book by clicking on the detected book titles and watch the relevant part of the video. This application result in time saving by the viewer. In order to achieve this application, a deep learning-based system was developed to retrieve the names of books from videos. YOLO-based method was used in the study. Different YOLO algorithms were used in the study, and YOLOv5 was found to be more successful. This study contributes to the field of text extraction and video analysis by developing a deep learning-based approach to extract book titles from book promotion videos.

 Extracting text from images and videos is an emerging field of research with a wide range of applications, including video search, video editing, and translation. Nowadays, book promotion videos in different languages are shared on social media and especially on YouTube. In this study; It is recommended to take book titles through book promotion videos. The developed system takes video as input and separates the names of the books. The viewer can select the desired book by clicking on the detected book titles and watch the relevant part of the video. This application result in time saving by the viewer. In order to achieve this application, a deep learning-based system was developed to retrieve the names of books from videos. YOLO-based method was used in the study. Different YOLO algorithms were used in the study, and YOLOv5 was found to be more successful. This study contributes to the field of text extraction and video analysis by developing a deep learning-based approach to extract book titles from book promotion videos.

Article Details

Extracting book titles from book recommendation videos using a deep learning approach

Authors:

Bartu Sarımehmetoğlu | Hamit Erdem

Publisher:

Kyrgyz-Turkish Manas University

Main Topics:

Electrical Engineering (Other)

Journal:

MANAS Journal of Engineering Vol.11 Issue 2, pp.229-234

Document Type:

Article

Publication Date:

12/2023

Document Language:

English

Document ID (Org No.):

2001306604

pISSN:

1694-7398

Book promotion videos

book titles

deep learning

YOLOv5

time saving

Issues

Article Details

Extracting book titles from book recommendation videos using a deep learning approach

Authors: Bartu Sarımehmetoğlu | Hamit Erdem

Publisher: Kyrgyz-Turkish Manas University

Main Topics: Electrical Engineering (Other)

Journal: MANAS Journal of Engineering Vol.11 Issue 2, pp.229-234

Document Type: Article

Publication Date: 12/2023

Document Language: English

Document ID (Org No.): 2001306604

pISSN: 1694-7398

Book promotion videos

book titles

deep learning

YOLOv5

time saving

Issues

Authors:

Bartu Sarımehmetoğlu | Hamit Erdem

Publisher:

Kyrgyz-Turkish Manas University

Main Topics:

Electrical Engineering (Other)

Journal:

MANAS Journal of Engineering Vol.11 Issue 2, pp.229-234

Document Type:

Article

Publication Date:

12/2023

Document Language:

English

Document ID (Org No.):

2001306604

pISSN:

1694-7398