Solar cells: Varieties and utilization-A short review

Akter, Raushanara; Mahin, Md. Mohaiminul Islam; Mahbub, Tauhidul; Nahreen, Kashphya; Raihan, Ahamed; Chakma, Rocky; Alam, M. J.; Mahtab, S. S.

doi:10.1063/5.0039501

Third International Conference on Material Science, Smart Structures and Applications: (ICMSS 2020) 2021

DOI: 10.1063/5.0039501

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Solar cells: Varieties and utilization-A short review

Raushanara Akter

Md. Mohaiminul Islam Mahin

Tauhidul Mahbub

et al.

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2024

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Cited by 1 publication

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Design and Implementation of Hand Gesture Detection System Using HM Model for Sign Language Recognition Development

Milu,

Fathima,

Talukder

et al. 2024

JDAIP

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Gesture detection is the primary and most significant step for sign language detection and sign language is the communication medium for people with speaking and hearing disabilities. This paper presents a novel method for dynamic hand gesture detection using Hidden Markov Models (HMMs) where we detect different English alphabet letters by tracing hand movements. The process involves skin color-based segmentation for hand isolation in video frames, followed by morphological operations to enhance image trajectories. Our system employs hand tracking and trajectory smoothing techniques, such as the Kalman filter, to monitor hand movements and refine gesture paths. Quantized sequences are then analyzed using the Baum-Welch Re-estimation Algorithm, an HMM-based approach. A maximum likelihood classifier is used to identify the most probable letter from the test sequences. Our method demonstrates significant improvements over traditional recognition techniques in real-time, automatic hand gesture recognition, particularly in its ability to distinguish complex gestures. The experimental results confirm the effectiveness of our approach in enhancing gesture-based sign language detection to alleviate the barrier between the deaf and hard-of-hearing community and general people.

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Design and Implementation of Hand Gesture Detection System Using HM Model for Sign Language Recognition Development

Milu,

Fathima,

Talukder

et al. 2024

JDAIP

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

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Solar cells: Varieties and utilization-A short review

Cited by 1 publication

References 17 publications

Design and Implementation of Hand Gesture Detection System Using HM Model for Sign Language Recognition Development

Design and Implementation of Hand Gesture Detection System Using HM Model for Sign Language Recognition Development

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