Donghyeok Park¹, Sumin Yeon², Hyeon Seo², Seok-Jun Buu², Suwon Lee^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2725-2737, 2025, DOI:10.32604/cmes.2025.061732 - 03 March 2025

Abstract Recent research on adversarial attacks has primarily focused on white-box attack techniques, with limited exploration of black-box attack methods. Furthermore, in many black-box research scenarios, it is assumed that the output label and probability distribution can be observed without imposing any constraints on the number of attack attempts. Unfortunately, this disregard for the real-world practicality of attacks, particularly their potential for human detectability, has left a gap in the research landscape. Considering these limitations, our study focuses on using a similar color attack method, assuming access only to the output label, limiting the number of More >

Arfa Siddiqu, Abdul Basit^*, Waheed Noor, Muhammad Asfandyar Khan, M. Saeed H. Kakar, Azam Khan

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 875-885, 2023, DOI:10.32604/iasc.2023.036426 - 29 April 2023

Abstract The optical character recognition for the right to left and cursive languages such as Arabic is challenging and received little attention from researchers in the past compared to the other Latin languages. Moreover, the absence of a standard publicly available dataset for several low-resource languages, including the Pashto language remained a hurdle in the advancement of language processing. Realizing that, a clean dataset is the fundamental and core requirement of character recognition, this research begins with dataset generation and aims at a system capable of complete language understanding. Keeping in view the complete and full… More >