All Outputs (10)

EAU-Net: A New Edge-Attention Based U-Net for Nationality Identification (2022)
Presentation / Conference Contribution

Identifying crime or individuals is one of the key tasks toward smart and safe city development when different nationals are involved. In this regard, identifying Nationality/Ethnicity through handwriting has received special attention. But due to fr... Read More about EAU-Net: A New Edge-Attention Based U-Net for Nationality Identification.

License Plate Number Detection in Drone Images (2022)
Journal Article

For an intelligent transportation system, identifying license plate numbers in drone photos is difficult, and it is used in practical applications like parking management, traffic management, automatically organizing parking spots, etc. The primary g... Read More about License Plate Number Detection in Drone Images.

An Augmented Reality-Based Approach for Designing Interactive Food Menu of Restaurant Using Android (2022)
Journal Article

The food industry is becoming competitive on a daily basis and introducing newer cuisines to the menu in an attempt to rise up the ladder. But they still are not being able to improve their performances because customers often only have the waiters t... Read More about An Augmented Reality-Based Approach for Designing Interactive Food Menu of Restaurant Using Android.

A Conformable Moments-Based Deep Learning System for Forged Handwriting Detection (2022)
Journal Article

Detecting forged handwriting is important in a wide variety of machine learning applications, and it is challenging when the input images are degraded with noise and blur. This article presents a new model based on conformable moments (CMs) and deep... Read More about A Conformable Moments-Based Deep Learning System for Forged Handwriting Detection.

Fake News Detection Techniques on Social Media: A Survey (2022)
Journal Article
Ali, I., Nizam Bin Ayub, M., Shivakumara, P., & Fazmidar Binti Mohd Noor, N. (2022). Fake News Detection Techniques on Social Media: A Survey. Wireless Communications and Mobile Computing, https://doi.org/10.1155/2022/6072084

Social media platforms like Twitter have become common tools for disseminating and consuming news because of the ease with which users can get access to and consume it. This paper focuses on the identification of false news and the use of cutting... Read More about Fake News Detection Techniques on Social Media: A Survey.

New Deep Spatio-Structural Features of Handwritten Text Lines for Document Age Classification (2022)
Journal Article
Shivakumara, P., Das, A., S. Raghunandan, K., Pal, U., & Blumenstein, M. (2022). New Deep Spatio-Structural Features of Handwritten Text Lines for Document Age Classification. International Journal of Pattern Recognition and Artificial Intelligence, 36(9), https://doi.org/10.1142/S0218001422520139

Document age estimation using handwritten text line images is useful for several pattern recognition and artificial intelligence applications such as forged signature verification, writer identification, gender identification, personality traits iden... Read More about New Deep Spatio-Structural Features of Handwritten Text Lines for Document Age Classification.

Local Resultant Gradient Vector Difference and Inpainting for 3D Text Detection in the Wild (2022)
Journal Article
Zhong, D., Shivakumara, P., Nandanwar, L., Pal, U., Blumenstein, M., & Lu, Y. (2022). Local Resultant Gradient Vector Difference and Inpainting for 3D Text Detection in the Wild. International Journal of Pattern Recognition and Artificial Intelligence, 36(8), Article 2253005. https://doi.org/10.1142/S0218001422530056

Three-dimensional (3D) text appearing in natural scene images is common due to 3D cameras and the capture of text from different angles, which presents new problems for text detection. This is because of the presence of depth information, shadows, an... Read More about Local Resultant Gradient Vector Difference and Inpainting for 3D Text Detection in the Wild.

A new ontology-based multimodal classification system for social media images of personality traits (2022)
Journal Article
Biswas, K., Shivakumara, P., Pal, U., & Lu, T. (2023). A new ontology-based multimodal classification system for social media images of personality traits. Signal, Image and Video Processing, 17, 543-551. https://doi.org/10.1007/s11760-022-02259-3

Number of users of social media is increasing exponentially. People are getting addicted to social media, and because of such addiction, it sometimes causes psychological and mental effects on the users. Understanding user interaction with social med... Read More about A new ontology-based multimodal classification system for social media images of personality traits.

An Episodic Learning Network for Text Detection on Human Bodies in Sports Images (2022)
Journal Article
Nath Chowdhury, P., Shivakumara, P., Raghavendra, R., Nag, S., Pal, U., Lu, T., & Lopresti, D. (2022). An Episodic Learning Network for Text Detection on Human Bodies in Sports Images. IEEE Transactions on Circuits and Systems for Video Technology, 32, 2279 - 2289. https://doi.org/10.1109/TCSVT.2021.3092713

Due to the proliferation of sports-related multimedia content on the WWW, effective visual search and retrieval present interesting research challenges. These are caused by poor image quality, a wide range of possible camera points of view, pose vari... Read More about An Episodic Learning Network for Text Detection on Human Bodies in Sports Images.

Multi‐gradient‐direction based deep learning model for arecanut disease identification (2022)
Journal Article
B. Mallikarjuna, S., Shivakumara, P., Khare, V., Basavanna, M., Pal, U., & Poornima, B. (2022). Multi‐gradient‐direction based deep learning model for arecanut disease identification. CAAI Transactions on Intelligence Technology, 7(2), 156–166. https://doi.org/10.1049/cit2.12088

Arecanut disease identification is a challenging problem in the field of image processing. In this work, we present a new combination of multi-gradient-direction and deep convolutional neural networks for arecanut disease identification, namely,... Read More about Multi‐gradient‐direction based deep learning model for arecanut disease identification.