Mr. Mounir Errami Profile

Mounir Errami

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 16 July 2019 Paper

Improving pedestrian detection using convolutional neural network and saliency detection

Mounir Errami, Mohammed Rziza, Abdelmoula Haboub

Proceedings Volume 11172, 111720K (2019) https://doi.org/10.1117/12.2522646

KEYWORDS: Convolutional neural networks, Feature extraction, Image classification, Neural networks, Convolution, Visualization, Classification systems

Read Abstract +

Convolutional neural networks have achieved excellent results in pedestrian detection state of the art. They are able to learn features from raw images which makes them easy, practical and robust for multiple visual classification tasks. In this paper, we propose a further improvement of convolutional neural networks using saliency detection. First, we use contourlet transform for saliency detection to generate a region of interest (ROI). The generated saliency maps are then used to feed the convolutional network which will be used for both feature extraction and classification. The paper contribution is two fold : (1) We use saliency detection as a filter to remove the noisy information in the background, which allow the network to converge faster during the training process. (2) Saliency reduced complexity of the road scene which improve significantly the CNN classification performance. Experiments conducted on INRIA and Pascal VOC datasets achieves state-of-the-art performance.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years