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Mondher Bouazizi, Chuheng Zheng, Siyuan Yang and Tomoaki Ohtsuki
A growing focus among scientists has been on researching the techniques of automatic detection of dementia that can be applied to the speech samples of individuals with dementia. Leveraging the rapid advancements in Deep Learning (DL) and Natural Languag...
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Salman Ibne Eunus, Shahriar Hossain, A. E. M. Ridwan, Ashik Adnan, Md. Saiful Islam, Dewan Ziaul Karim, Golam Rabiul Alam and Jia Uddin
Accidents due to defective railway lines and derailments are common disasters that are observed frequently in Southeast Asian countries. It is imperative to run proper diagnosis over the detection of such faults to prevent such accidents. However, manual...
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Marya Butt, Nick Glas, Jaimy Monsuur, Ruben Stoop and Ander de Keijzer
Scoring targets in shooting sports is a crucial and time-consuming task that relies on manually counting bullet holes. This paper introduces an automatic score detection model using object detection techniques. The study contributes to the field of compu...
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Fenfang Li, Zhengzhang Zhao, Li Wang and Han Deng
Sentence Boundary Disambiguation (SBD) is crucial for building datasets for tasks such as machine translation, syntactic analysis, and semantic analysis. Currently, most automatic sentence segmentation in Tibetan adopts the methods of rule-based and stat...
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Woonghee Lee, Mingeon Ju, Yura Sim, Young Kul Jung, Tae Hyung Kim and Younghoon Kim
Deep learning-based segmentation models have made a profound impact on medical procedures, with U-Net based computed tomography (CT) segmentation models exhibiting remarkable performance. Yet, even with these advances, these models are found to be vulner...
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