Sign Language Recognition Using Deep Learning: Advancements and Challenges

International Journal of Latest Technology in Engineering Management & Applied Science, Год журнала: 2025, Номер 13(12), С. 318 - 324

Опубликована: Янв. 21, 2025

Abstract: Sign language recognition (SLR) has arisen as a major area of research in recent years, attempting to bridge the communication gap between deaf and hard-of-hearing community hearing world. This study addresses construction implementation manual alphabet system utilising deep learning techniques, notably convolutional neural networks (CNNs). The work focuses on establishing an efficient accurate for converting Nigerian Language alphabets into text. By integrating computer vision machine methods, proposed seeks overcome individuals. paper explains technique adopted, including data collection, preprocessing, model architecture, deployment using web-based tools. achieves 95% success rate recognizing static hand motions, proving its potential real-world applications. However, issues identifying dynamic motions generalizing across varied user populations are observed. report finishes with recommendations future research, emphasizing need combining temporal analysis expanding system's capabilities word phrase recognition.

Язык: Английский

---

From pixels to letters: A high-accuracy CPU-real-time American Sign Language detection pipeline

Machine Learning with Applications, Год журнала: 2025, Номер unknown, С. 100650 - 100650

Опубликована: Апрель 1, 2025

Язык: Английский

---

Sign Language Detection Dataset: A Resource for AI-Based Recognition Systems

Data in Brief, Год журнала: 2025, Номер unknown, С. 111703 - 111703

Опубликована: Май 1, 2025

Язык: Английский

---

Real-Time Detection of Turkish Sign Language Letters and Numbers with Deep Learning

Academic Platform Journal of Engineering and Smart Systems, Год журнала: 2025, Номер 13(2), С. 31 - 41

Опубликована: Май 30, 2025

The visual language that hearing or speech-impaired individuals communicate with through facial expressions and hand movements is called sign language. rate of reading writing very low. For this reason, have great difficulty in communicating other people, especially when benefiting from services such as hospitals education. In study, real-time detection display on the computer screen were performed deep learning. shown their hands fingers are detected front camera. As a result detection, letter corresponding to movement recognized displayed screen. YOLOv8 architecture was used method. First, data set created for study. consists 29 letters 10 numbers. Photographs 100 different people taken set. Different changes made photographs With these additions, error may occur due any distortion camera minimized. photographs, number forming increased 11079. average stability 90.7%, mAP 85.8%, recall 81.4%.

Язык: Английский

---

Hand Gesture Recognition Using Deep Learning

International Journal of Innovative Science and Research Technology (IJISRT), Год журнала: 2024, Номер unknown, С. 69 - 72

Опубликована: Авг. 13, 2024

Hand gesture recognition (HGR) has gained significant attention due to its potential for various applications. This paper explores the use of deep learning, specifically Convolutional Neural Networks (CNNs), HGR using TensorFlow library. We investigate existing research on CNN-based HGR, focusing image classification tasks. then provide a brief overview CNNs and their suitability recognition. Subsequently, we describe typical workflow learning-based system, including data preprocessing, hand detection, feature extraction with CNNs, classification. highlight advantages build train CNN models HGR. Finally, conclude by summarizing key findings from related work mentioning specific dataset number gestures classified in our research. contributes growing body emphasizes developing accurate efficient systems.

Язык: Английский

---

Artificial intelligence in sign language recognition: A comprehensive bibliometric and visual analysis

Computers & Electrical Engineering, Год журнала: 2024, Номер 120, С. 109854 - 109854

Опубликована: Ноя. 14, 2024

Язык: Английский

---

Sign Language Interpretation in Live Streams Using MediaPipe with Hybrid Deep Learning Model

Опубликована: Окт. 4, 2024

Язык: Английский

---