Awais Ahmad¹, Sohail Jabbar^1,*, Sheeraz Akram¹, Anand Paul², Umar Raza³, Nuha Mohammed Alshuqayran¹

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3129-3150, 2024, DOI:10.32604/cmc.2024.045385

Abstract This paper presents an innovative approach to enhance the querying capability of ChatGPT, a conversational artificial intelligence model, by incorporating voice-based interaction and a convolutional neural network (CNN)-based impaired vision detection model. The proposed system aims to improve user experience and accessibility by allowing users to interact with ChatGPT using voice commands. Additionally, a CNN-based model is employed to detect impairments in user vision, enabling the system to adapt its responses and provide appropriate assistance. This research tackles head-on the challenges of user experience and inclusivity in artificial intelligence (AI). It underscores our commitment to overcoming these obstacles, making ChatGPT… More >

Hong Zhang^1,*, Haijian Shao²

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2061-2102, 2024, DOI:10.32604/cmes.2023.030649

Abstract OpenAI and ChatGPT, as state-of-the-art language models driven by cutting-edge artificial intelligence technology, have gained widespread adoption across diverse industries. In the realm of computer vision, these models have been employed for intricate tasks including object recognition, image generation, and image processing, leveraging their advanced capabilities to fuel transformative breakthroughs. Within the gaming industry, they have found utility in crafting virtual characters and generating plots and dialogues, thereby enabling immersive and interactive player experiences. Furthermore, these models have been harnessed in the realm of medical diagnosis, providing invaluable insights and support to healthcare professionals in the realm of disease detection.… More > Graphic Abstract

Ou Ye^1,2, Mimi Wang¹, Zhenhua Yu^1,*, Yan Fu¹, Shun Yi¹, Jun Deng²

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5675-5696, 2023, DOI:10.32604/cmc.2023.037503

Abstract Currently, the video captioning models based on an encoder-decoder mainly rely on a single video input source. The contents of video captioning are limited since few studies employed external corpus information to guide the generation of video captioning, which is not conducive to the accurate description and understanding of video content. To address this issue, a novel video captioning method guided by a sentence retrieval generation network (ED-SRG) is proposed in this paper. First, a ResNeXt network model, an efficient convolutional network for online video understanding (ECO) model, and a long short-term memory (LSTM) network model are integrated to construct… More >

Inshirah Ali AlMutairi^*, Ali Mustafa Qamar

Journal on Artificial Intelligence, Vol.4, No.3, pp. 155-165, 2022, DOI:10.32604/jai.2022.032390

Abstract Neural talk models play a leading role in the growing popular building of conversational managers. A commonplace criticism of those systems is that they seldom understand or use the conversation data efficiently. The development of profound concentration on innovations has increased the use of neural models for a discussion display. In recent years, deep learning (DL) models have achieved significant success in various tasks, and many dialogue systems are also employing DL techniques. The primary issues involved in the generation of the dialogue system are acquiring perspectives into instinctual linguistics, comprehension provision, and conversation assessment. In this paper, we mainly… More >

Bao Rong Chang^1,*, Hsiu-Fen Tsai², Po-Wen Su¹

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 253-277, 2021, DOI:10.32604/cmes.2021.015673

Abstract This paper introduces a novel transform method to produce the newly generated programs through code transform model called the second generation of Generative Pre-trained Transformer (GPT-2) reasonably, improving the program execution performance significantly. Besides, a theoretical estimation in statistics has given the minimum number of generated programs as required, which guarantees to find the best one within them. The proposed approach can help the voice assistant machine resolve the problem of inefficient execution of application code. In addition to GPT-2, this study develops the variational Simhash algorithm to check the code similarity between sample program and newly generated program, and… More >