The application and development of Integrated Surface Subsurface Hydrological Models (ISSHMs) have grown in the last few decades thanks to the advent of High-Performance Computing (HPC) infrastructures, the ...
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Identifying the neural substrates of human auditory system has been a classic pursuit that fell into the list of grand challenges in neuroscience. Deep learning and natural language processing towards the end of the l...
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In this paper a reduced-switch high-frequency isolated single-phase buck-boost AC-AC converter without commutation issue, is proposed. The proposed converter produces both inverting and non-inverting output voltages i...
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Keyloggers are malicious software programs that record keystrokes of users without their consent or knowledge. They can steal sensitive information like credit card numbers and passwords. They pose a significant threa...
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Considering the concept of a Circular Economy, which entails several life cycles of, e.g., vehicles, their components, and materials, it is important to investigate how the respective Digital Twins are managed over th...
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A research investigates how assistants function as chatbots. These tech gadgets represent a rare and fortunate connection between people and technology. Speechenabled Chatbots or AI-driven systems revolutionize the in...
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This study presents the development of a mobile application for classifying skin conditions into Melanoma, Acne, and Healthy skin. A dataset of 214 Melanoma images from Dermnet, 395 Acne images, 400 Healthy skin image...
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This study examines the role of artificial intelligence (AI) in supply chain management (SCM) through a comprehensive bibliometric analysis of literature sourced from the Scopus database, renowned for its extensive an...
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There is a growing concern about adversarial attacks against automatic speech recognition (ASR) systems. Although research into targeted universal adversarial examples (AEs) has progressed, current methods are constra...
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Approximately 70 million individuals globally utilize sign languages as a means of communication due to their hearing impairment. The study undertaken in sign languages is extensive and fruitful. However, there are ov...
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ISBN:
(纸本)9781510688278
Approximately 70 million individuals globally utilize sign languages as a means of communication due to their hearing impairment. The study undertaken in sign languages is extensive and fruitful. However, there are over 300 sign languages worldwide, but most research focuses on a single language [1]. Creating AI models for sign language challenges sometimes requires large datasets, which can be difficult to produce. Various research has produced datasets for sign language using various methodologies;nevertheless, they often focus on specific sign languages. Developing hand skeleton templates for sign languages provides a more efficient method than creating numerous instances of distinct signs. By creating a basic framework or structure, it becomes much simpler to utilize generative models, like GANs[2], to generate a wide range of different versions of the framework. These generative models can effectively reproduce and adjust the fundamental structures into many sign language forms, capturing the diversity in hand shapes, orientations, and movements necessary for precise sign representation. The main objective of our research is to develop a conditional generative adversarial network (cGAN) model that can generate hand images based on hand skeletons;this approach not only improves the capacity to generate sign language data on a larger scale, but also guarantees uniformity across different versions of signs. This makes it easier to create sign language recognition systems that are more reliable and flexible. To train this model, we devised a web scraping technique that produced a significant collection of hand photos taken from TED lecture recordings, together with their corresponding skeletons. Our created cGAN-based model allows researchers to generate artificial hand images by employing target skeleton inputs. This enables the creation of extensive datasets for sign language. Our contribution is expected to streamline the exploration of additional sign languages
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