Amir Hussain

Feb 13, 2025 | onlinelibrary.wiley.com | Siva Sai |Vinay Chamola |Amir Hussain |Keya Arunakar

1 Introduction Generative artificial intelligence (GAI) is a form of artificial intelligence (AI) technology that can generate text, images, audio, and synthetic data, among other content types. The recent chatter around GAI has been driven by the simplicity of new user interfaces for creating high-quality text, graphics, and videos in seconds. It should be noted that the technology is familiar. Chatbots introduced GAI in the 1960s.

Dec 3, 2024 | nature.com | Muhammad Usman |Amir Hussain |Muhammad Imran |Qammer Hussain Abbasi |Jalil ur Rehman Kazim |Hira Hameed | +2 more

In recent years, Lip-reading has emerged as a significant research challenge. The aim is to recognise speech by analysing Lip movements. The majority of Lip-reading technologies are based on cameras and wearable devices. However, these technologies have well-known occlusion and ambient lighting limitations, privacy concerns as well as wearable device discomfort for subjects and disturb their daily routines. Furthermore, in the era of coronavirus (COVID-19), where face masks are the norm, vision-based and wearable-based technologies for hearing aids are ineffective. To address the fundamental limitations of camera-based and wearable-based systems, this paper proposes a Radio Frequency Identification (RFID)-based smart mask for a Lip-reading framework capable of reading Lips under face masks, enabling effective speech recognition and fostering conversational accessibility for individuals with hearing impairment. The system uses RFID technology to make Radio Frequency (RF) sensing-based Lip-reading possible. A smart RFID face mask is used to collect a dataset containing three different classes of vowels (A, E, I, O, U), Consonants (F, G, M, S), and words (Fish, Goat, Meal, Moon, Snake). The collected data are fed into well-known machine-learning models for classification. A high classification accuracy is achieved by individual classes and combined datasets. On the RFID combined dataset, the Random Forest model achieves a high classification accuracy of 80%.

Nov 19, 2024 | mdpi.com | Lu Chen |Amir Hussain |Yu Xin Liu |Jie Tan

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Oct 10, 2024 | mdpi.com | Amir Hussain Idrisi |Amir Hussain

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.

Sep 14, 2024 | onlinelibrary.wiley.com | Peng Liang |Hang Tu |Amir Hussain |Ziyuan Li

CONFLICT OF INTEREST The authors declare no conflict of interest. REFERENCES (1993). Multitask learning: A knowledge-based source of inductive bias. In International Conference on Machine Learning (pp. 41–48). Morgan Kaufmann Publishers Inc. , , , , & (2021). A serial image copy-move forgery localization scheme with source/target distinguishment. IEEE Transactions on Multimedia, 23, 3506–3517. https://doi.org/10.1109/TMM.2020.3026868 , , & (2015).