Search Results - KuSL2023: A CNN-Based Recognition Method for Kurdish Sign Language Detection and Classification

An Intelligent Kurdish Sign Language Recognition System Based on Tuned CNN by Ahmed, Hunar Abubakir, Mustafa, Sazgar Yassin, Braim, Sumaya Zrar, Rasull, Razawa Mohammed

“… However, designing a system that can automatically identify the signs of Kurdish sign language is a challenging task, especially for Kurdish sign language…”
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Improved Recognition of Kurdish Sign Language Using Modified CNN by Hama Rawf, Karwan Mahdi Hama, Abdulrahman, Ayub Othman, Mohammed, Aree Ali

“…The deaf society supports Sign Language Recognition (SLR) since it is used to educate individuals in communication, education, and socialization…”
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Wearable Electronic Glove and Multilayer Para-LSTM-CNN-Based Method for Sign Language Recognition by Wang, Dapeng, Wang, Mingyuan, Zhang, Ziqi, Liu, Teng, Meng, Chuizhou, Guo, Shijie

“… Wearable sign language recognition systems, especially those based on flexible electronic glove, have attracted much attention due to their efficiency for sign language recognition…”
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Efficient Kinect Sensor-based Kurdish Sign Language Recognition Using Echo System Network by Mirza, Sami F., Al-Talabani, Abdulbasit K.

“… Automatic sign language recognition (ASLR) is a field that has recently been studied for various sign languages…”
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Attention-Based 3D-CNNs for Large-Vocabulary Sign Language Recognition by Huang, Jie, Zhou, Wengang, Li, Houqiang, Li, Weiping

“…Sign language recognition (SLR) is an important and challenging research topic in the multimedia field…”
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American Sign Language Recognition and Generation : A CNN-based Approach by Pusti Sheth, Ronik Dedhia, Akshit Chheda, Dr. Vinaya Sawant

“… In this paper, we present a real-time American Sign Language (ASL) generation and recognition system that makes use of Convolutional Neural Networks and deep learning (CNNs…”
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Arabic Sign Language Recognition using Lightweight CNN-based Architecture by AlKhuraym, Batool Yahya, Ismail, Mohamed Maher Ben, Bchir, Ouiem

“… communities. Designing and implementing a novel Arabic Sign Language (ArSL) recognition system would significantly affect their quality of life…”
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CNN based Sign Language Recognition System with Multi-format Output by Pandey, Harshit, Ahmed, Amaan, Kumar, Tushar, Singh, Vaibhav Kumar, Dutta, Lipika, Yadav, Pinki

“… in it. In this article a real time method for sign recognition using neural networks for finger spelling based on American sign language is presented…”
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Prediction of sign language recognition based on multi layered CNN by Arun Prasath, G, Annapurani, K

“…Sign Language Recognition (SLR) helps to bridge the gap between ordinary and hearing-impaired people…”
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Efficient CNN Based Sign Language Recognition System Using Optimization Technique by O G, Manukumaar, Naveen, Soumyalatha, U M, Ashwinkumar

“…Convolutional Neural Network (CNN) - based sign language recognition has significant importance in bridging communication gaps between individuals who are deaf or hard of hearing and the general population…”
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Regional-CNN-based enhanced Turkish sign language recognition by Yirtici, Tolga, Yurtkan, Kamil

“… Automatically detecting and recognizing sign languages by computers are also possible applications…”
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Sign Language Recognition Based on CNN-BiLSTM Using RF Signals by Zhang, Yajun, Wang, Yuankang, Li, Feng, Yu, Weiqian, Wang, Congcong, Jiang, Ying

“…As the number of individuals with speech and hearing impairments continues to grow, the demand for sign language recognition systems is increasing…”
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Hand Keypoint-Based CNN for SIBI Sign Language Recognition by Handayani, Anik Nur, Amaliya, Sholikhatul, Akbar, Muhammad Iqbal, Wiryawan, Muhammad Zaki, Liang, Yeoh Wen, Kurniawan, Wendy Cahya

“…) for SIBI classification. The research utilizes Kinect 2.0 for precise data collection, enabling accurate hand keypoint detection and preprocessing…”
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Sign Language Recognition Based on CNN and Data Augmentation by Li, Gaoyun, Wang, Xiong, Liu, Yong

“…Sign language recognition is an important assistive communication technology, which is one of the main communication methods for hearing and language impaired individuals…”
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Multi modal spatio temporal co-trained CNNs with single modal testing on RGB–D based sign language gesture recognition by Ravi, Sunitha, Suman, Maloji, Kishore, P.V.V., Kumar E, Kiran, Kumar M, Teja Kiran, Kumar D, Anil

“… Extracting hand movements using single RGB video camera for sign language recognition is a necessary attribute in developing an automated sign language recognition system…”
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Traffic Sign Recognition Method Based on Dual-Channel CNN by Zhao, Zeyi, Zhou, Fuqiang, Wang, Shaohong, Xu, Xiaoli, Chao, Fenjin, Lin, Zhoupeng

“…Aiming at traffic sign problem, the traditional LeNet-5 network structure has low accuracy of traffic sign recognition, slow identification speed and ignores natural factors such as weather…”
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CNN based Approach for Sign Recognition in the Indian Sign language by Unkule, Pranav, Shinde, Chatak, Saurkar, Pratik, Agarkar, Sanchit, Verma, Usha

“… Communication between people with speech impairment and non-signers becomes difficult as they tend to use Sign Language…”
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Isolated Video-Based Sign Language Recognition Using a Hybrid CNN-LSTM Framework Based on Attention Mechanism by Kumari, Diksha, Anand, Radhey Shyam

“… Sign language recognition (SLR) is a popular research domain as it provides an efficient and reliable solution to bridge the communication gap between people who are hard of hearing and those with good hearing…”
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Multimodal Fusion for Thai Sign Language Recognition: Integrating RGB-Based CNN and Landmark-Based Features for Enhanced Gesture Recognition by Vijitkunsawat, Wuttichai, Sopin, Anan, Sathusen, Anusorn

“…This paper introduces a multimodal fusion model designed to improve the recognition of Thai Sign Language (TSL…”
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Chinese Sign Language Recognition Based on Two-stream CNN and LSTM Network by LUOYin, Ying, HU, LIUDi-kun, LIRui, YANGMeng-hao

“… This paper takes Chinese sign language words as the research object, and proposes a new method of sign language recognition based on two-stream 3D-CNN and LSTM network…”
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