Search

Your search keyword '"Dutta, Vibekananda"' showing total 33 results
Start Over Author "Dutta, Vibekananda"
33 results on '"Dutta, Vibekananda"'

2. Analysis and Recognition of Human Postures for Robotic Applications

Author

Morawski, Maciej, Zielinska, Teresa, Awong, Lisiane Esther Ekemeyong, Dutta, Vibekananda, Ceccarelli, Marco, Series Editor, Agrawal, Sunil K., Advisory Editor, Corves, Burkhard, Advisory Editor, Glazunov, Victor, Advisory Editor, Hernández, Alfonso, Advisory Editor, Huang, Tian, Advisory Editor, Jauregui Correa, Juan Carlos, Advisory Editor, Takeda, Yukio, Advisory Editor, and Okada, Masafumi, editor

Published
2023
Full Text
View/download PDF

3. Hybrid Model for Improving the Classification Effectiveness of Network Intrusion Detection

Author

Dutta, Vibekananda, Choraś, Michał, Kozik, Rafał, Pawlicki, Marek, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Herrero, Álvaro, editor, Cambra, Carlos, editor, Urda, Daniel, editor, Sedano, Javier, editor, Quintián, Héctor, editor, and Corchado, Emilio, editor

Published
2021
Full Text
View/download PDF

4. Networking technologies for robotic applications

Author

Dutta, Vibekananda and Zielinska, Teresa

Subjects
Computer Science - Computers and Society, Computer Science - Cryptography and Security, Computer Science - Robotics
Abstract

The ongoing progress in networking security, together with the growing range of robot applications in many fields of everyday life, makes robotics tangible reality in our near future. Accordingly, new advanced services, depends on the interplay between the robotics and cyber security, are being an important role in robotics world. This paper addresses technological implications of security enhancement to the Internet of Thing (IoT)-aided robotics domain, where networked robots are expected to work in complex environments. The security enhancement suggested by the NIST (National Institute of Standards and Technology) creates a security template for secure communications over the network are also discussed., Comment: Conference

Published
2015

6. Novel Architecture for 3D model in virtual communities from detected face

Author

Dutta, Vibekananda, Kesswani, Dr Nishtha, and Gahalot, Deepti

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

In this research paper we suggest how to extract a face from an image, modify it, characterize it in terms of high-level properties, and apply it to the creation of a personalized avatar. In this research work we tested, we implemented the algorithm on several hundred facial images, including many taken under uncontrolled acquisition conditions, and found to exhibit satisfactory performance for immediate practical use., Comment: 7 pages

Published
2012

12. Predicting the Intention of Human Activities for Real-Time Human-Robot Interaction (HRI)

Author

Dutta, Vibekananda, Zielinska, Teresa, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Agah, Arvin, editor, Cabibihan, John-John, editor, Howard, Ayanna M., editor, Salichs, Miguel A., editor, and He, Hongsheng, editor

Published
2016
Full Text
View/download PDF

13. Improved Competitive Neural Network for Classification of Human Postures Based on Data from RGB-D Sensors

Author

Dutta, Vibekananda, Cydejko, Jakub, and Zielińska, Teresa

Abstract

The cognitive goal of this paper is to assess whether marker-less motion capture systems provide sufficient data to recognize human postures in the side view. The research goal is to develop a new posture classification method that allows for analysing human activities using data recorded by RGB-D sensors. The method is insensitive to recorded activity duration and gives satisfactory results for the sagittal plane. An improved competitive Neural Network (cNN) was used. The method of preprocessing the data is first discussed. Then, a method for classifying human postures is presented. Finally, classification quality using various distance metrics is assessed. The data sets covering the selection of human activities have been created. Postures typical for these activities have been identified using the classifying neural network. The classification quality obtained using the proposed cNN network and two other popular neural networks were compared. The results confirmed the advantage of cNN network. The developed method makes it possible to recognize human postures by observing movement in the sagittal plane.

Published
2024
Full Text
View/download PDF

14. Improved Competitive Neural Network for Classification of Human Postures Based on Data from RGB-D Sensors.

Author

Dutta, Vibekananda, Cydejko, Jakub, and Zielińska, Teresa

Subjects
*MOTION capture (Human mechanics), *POSTURE, *HUMAN activity recognition, *ANATOMICAL planes, *DETECTORS, *DATA recorders & recording, *HUMAN beings
Abstract

The cognitive goal of this paper is to assess whether marker-less motion capture systems provide sufficient data to recognize human postures in the side view. The research goal is to develop a new posture classification method that allows for analysing human activities using data recorded by RGB-D sensors. The method is insensitive to recorded activity duration and gives satisfactory results for the sagittal plane. An improved competitive Neural Network (cNN) was used. The method of preprocessing the data is first discussed. Then, a method for classifying human postures is presented. Finally, classification quality using various distance metrics is assessed. The data sets covering the selection of human activities have been created. Postures typical for these activities have been identified using the classifying neural network. The classification quality obtained using the proposed cNN network and two other popular neural networks were compared. The results confirmed the advantage of cNN network. The developed method makes it possible to recognize human postures by observing movement in the sagittal plane. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results