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Fingerspelling Identification For American Sign Language Based On Resnet-18
2021
International journal of advanced networking and applications
Sign language as the main communication channel for deaf and hearing people, plays a very important role in daily life. With the rapid development of the field of deep learning, the field of sign language recognition has ushered in new opportunities. Aiming at the small number of sign language samples and low detection accuracy, an American sign language detection method based on Resnet-18 and data augmentation is proposed. First, the sign language picture is adjusted to 64×64 size using the
doi:10.35444/ijana.2021.13102
fatcat:y6ch5wjvungkvi7zghjfsfee2i