TY - GEN
T1 - Interactive System for Toddlers Using Doodle Recognition
AU - Gagandeep, K. N.
AU - Belagali, Atharv R.
AU - Rashmi, M.
AU - Guddeti, Ram Mohana Reddy
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - Typing using the keyboard or using a mouse is hard for small children. In this paper, we proposed an interactive system to improve the learning ability of a toddler. The proposed doodle recognition system provides an attractive and efficient way to interact toddlers with computer systems by following the Human-Computer Interaction guidelines and deep learning. The most common practice that toddlers develop is scribbling random images, so we decided to use this skill to provide a gateway for the toddlers to interact thus and learning with computers by using our proposed simple interface. When the toddler (user) starts to scribble or draw something on the screen, whiteboard, or paper; the application goes into input mode, and as soon as the drawing is stopped the image on the screen or whiteboard is processed by the trained CNN model and the action is carried out based on the output of the model.
AB - Typing using the keyboard or using a mouse is hard for small children. In this paper, we proposed an interactive system to improve the learning ability of a toddler. The proposed doodle recognition system provides an attractive and efficient way to interact toddlers with computer systems by following the Human-Computer Interaction guidelines and deep learning. The most common practice that toddlers develop is scribbling random images, so we decided to use this skill to provide a gateway for the toddlers to interact thus and learning with computers by using our proposed simple interface. When the toddler (user) starts to scribble or draw something on the screen, whiteboard, or paper; the application goes into input mode, and as soon as the drawing is stopped the image on the screen or whiteboard is processed by the trained CNN model and the action is carried out based on the output of the model.
UR - https://www.scopus.com/pages/publications/85200679522
UR - https://www.scopus.com/pages/publications/85200679522#tab=citedBy
U2 - 10.1007/978-3-031-12700-7_61
DO - 10.1007/978-3-031-12700-7_61
M3 - Conference contribution
AN - SCOPUS:85200679522
SN - 9783031126994
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 597
EP - 606
BT - Pattern Recognition and Machine Intelligence - 9th International Conference, PReMI 2021, Proceedings
A2 - Ghosh, Ashish
A2 - Bhattacharyya, Malay
A2 - Sankar Ray, Shubhra
A2 - K. Pal, Sankar
A2 - King, Irwin
PB - Springer Science and Business Media Deutschland GmbH
T2 - 9th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2021
Y2 - 15 December 2021 through 18 December 2021
ER -