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30 articles for “Sign language recognition”
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An Automation Detection for Sign Language Using AI
Abstract: Sign language recognition has attracted considerable interest because of its ability to facilitate communication between the deaf community and the public, thereby bridging communication divides. Traditional approaches to sign language recognition often face challenges in accurately interpreting the complex and nuanced gestures inherent in sign languages. However, recent advancements in deep learning techniques have shown promising results in improving the accuracy and robustness of sign language recognition systems. This study …
Published in Recent Trends in Programming languages · Vol. 11, Issue 1, 2024 · pp. 1–14 Read article
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Sign Language and Face Expression Recognition Using Neural Networks: Deep Learning Approach to Break Communication Barriers
Abstract: Our study proposes a multimodal gesture recognition system specifically designed to aid communication for the deaf community. By employing neural network concepts, we utilize 3D convolutional neural networks (3D CNNs) to extract features from both hand and face images, focusing on relevant regions. Preprocessing techniques are applied to isolate these areas of interest prior to feature extraction. Unique 3D CNN architectures are then trained for each modality to capture the …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 1–10 Read article
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Air Touch Mouse Interface
Abstract: The “Air Touch Mouse Interface” introduces a groundbreaking method for human–computer interaction (HCI) by utilizing hand gestures captured through web cameras to control cursor movements without physical input devices. This project investigates the feasibility and effectiveness of employing image processing techniques to interpret hand gestures as mouse inputs, thereby enhancing the accessibility and versatility of computing interfaces. By eliminating the dependency on traditional mice and mouse pads, the proposed interface …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 1, 2024 · pp. 1–16 Read article
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Sign Language to Speech Translation and Emergency Alert System for Dumb persons using Ml and IOT
Abstract: This project proposes a novel approach for gesture recognition using key point extraction and neural networks. Our proposed system leverages key point extraction techniques to capture fine-grained spatial information from input gestures. These key points are then fed into a neural network model, allowing for automatic feature learning and robust gesture classification. The goal of this project is to integrate OpenCV's computer vision capabilities to build a flexible and effective …
Published in Journal of Microcontroller Engineering and Applications · Vol. 11, Issue 2, 2024 · pp. 17–21 Read article
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Sign Talk for Blind and Deaf Translating Hand Gestures into Audible and Textual Communication
Abstract: Sign language serves as a vital communication method for individuals who are deaf or have hearing impairments. It relies on hand gestures, facial cues, and body language to convey messages and express meaning. However, many people who do not know sign language find it hard to communicate with sign language users. The latest progress in artificial intelligence and computing has enabled the creation of systems that can automatically recognize sign …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 2, 2025 · pp. 20–26 Read article
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Sign Language-enabled Offline IP-based Video Call Intercom System for the Deaf
Abstract: Individuals who are deaf or hard of hearing frequently encounter major communication challenges on digital platforms because sign language support is often insufficient. This study presents a real-time, internet-independent sign language-to-text translation system embedded in an offline IP-based video intercom, designed to facilitate seamless communication. Leveraging TensorFlow’s Convolutional Neural Network (CNN) for classification and MediaPipe for hand tracking, the system achieved a training accuracy of 94.24% and a validation accuracy …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 53–66 Read article
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Real-Time Gesture Recognition with Convolutional Neural Networks
Abstract: Sign language detection plays a pivotal role in bridging communication barriers for the deaf and hard of hearing community. An extensive investigation on the use of convolutional neural networks (CNNs) for sign language recognition is presented in this article. Leveraging the power of deep learning, our research aims to develop an accurate and efficient system capable of recognizing and classifying sign language gestures in real-time. The report begins with an …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 2, 2024 · pp. 12–18 Read article
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Integrating Deep Learning and Computer Vision for Recognizing American Sign Language
Abstract: The only way the hearing-impaired community can exchange ideas is by utilizing non-verbal communication. The main challenge, however, is that the non-impaired community, which may not comprehend non-verbal communication, would struggle to communicate effectively with this group, and vice versa. The project is purposely devised to admit unwilling and dumb societies to transport ideas and connect with the organization. It aims to bridge the gap between the hearing- and speech-impaired …
Published in Current Trends in Information Technology · Vol. 14, Issue 3, 2024 · pp. 10–17 Read article
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A Study of ROI Based Sign Language to Text Translation in Real Time Using Deep Learning
Abstract: Since sign language is their primary form of communication, it plays a significant role in the lives of hearing and speech disabled people. However, since not everyone is conversant in sign language, it is challenging for the disabled to interact with others daily. Sign language is made up of a variety of hand gestures that may stand in for a wide range of words and sentiments. The purpose of this …
Published in International Journal of Optical Innovations & Research · Vol. 1, Issue 1, 2023 · pp. 8–14 Read article
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Real-Time Sign Language to Speech Conversion Glove Using Arduino and Wearable Sensors
Abstract: This research work presents the design and development of a low-cost, wearable glove system for real- time sign language to speech conversion. The system employs an Arduino microcontroller integrated with flex sensors and an accelerometer to accurately detect hand gestures. The system translates hand gestures into audible speech through Bluetooth communication, enabling seamless interaction for hearing-impaired individuals. By converting sign language into speech in real-time, it significantly enhances communication accessibility …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 14, Issue 3, 2025 · pp. 10–18 Read article
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Emotion Recognition from Electroencephalogram Signal and Eye Movement Based on Deep Learning
Abstract: Emotion recognition from electroencephalogram (EEG) signals has gained significant attention due to its potential in human- computer interaction (HCI), mental health monitoring, and personalized content delivery. This paper presents the use of Convolutional neural networks (CNNs) to classify emotions such as happiness, sadness, fear, neutral, and disgust by leveraging a fusion of EEG signals and eye movements data. Compared to conventional methods of emotion detection, such as those that rely …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 8–15 Read article
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Hand Gesture Recognition Systems: A Review of Vision-based and Sensor-based Approaches
Abstract: With many real-world uses, such as sign language translation and human-computer interaction, hand gesture detection is a crucial area of study in the science of computer vision. In this study, we propose a Convolutional Neural Network (CNN) model that uses real-time camera images to recognise hand gestures. A collection of hand motion photographs spanning the English alphabet (A-Z) was gathered, and the images were pre-processed to exclude any backdrop and …
Published in International Journal of Optical Innovations & Research · Vol. 1, Issue 1, 2023 · pp. 15–20 Read article
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Integrated Qualitative Response Assessment System
Abstract: Examinations for universities and yearboards are traditionally administered offline, with a significant number of students opting for subjective exams. This preference stems from the labor-intensive nature of evaluating subjective responses, which requires considerable time and effort from educators. Additionally, subjective grading can be influenced by the evaluator’s mood, leading to inconsistencies. In contrast, multiple-choice and objective questions are prevalent in entrance and competitive exams due to their ease of automated …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 3, 2024 · pp. 18–24 Read article
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Unravelling the Impact of AI: Insights into Pattern Recognition and Image Processing
Abstract: Apart from its academic origins, the evolution of Artificial Intelligence (AI) has emerged as a notable influence in shaping our daily experiences. Artificial intelligence, which focuses on domains such as image processing and pattern recognition, encompasses a vast array of topics, including its complex applications, obstacles, and societal repercussions. Machine Learning, Natural Language Processing, Computer Vision, Robotics, Expert Systems, Knowledge Representation, and AI Ethics are among the domains in which …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 1, 2024 · pp. 1–7 Read article
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Using Artificial Intelligence to Identify Emotional Neglect and Manage Emotional Well-Being: A New Perspective on Enhancing Mental Health
Abstract: Background: The rising prevalence of mental health issues, coupled with a shortage of qualified professionals, necessitates innovative solutions, especially considering the lasting impact of childhood emotional neglect. Emotional neglect, one of the most profound forms of maltreatment, is a widespread concern that significantly affects an individual’s mental health and overall well-being in the long term. Aim: The purpose of this research article is to explore the capability of artificial intelligence …
Published in International Journal of Behavioral Sciences · Vol. 2, Issue 1, 2025 · pp. 1–7 Read article
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Survey Paper on Multilingual Live Call Translation Using Deep Learning
Abstract: This research work surveys cutting-edge language translation technologies, including multi-lingual, real-time translation, voice recognition, speech-to-text conversion, and transcription in the hearing process. The study explores the complex mechanisms behind voice call language translation, focusing on sophisticated machine learning models integrated with cloud-based or local applications to facilitate seamless communication across language barriers. Furthermore, conducting research in live communication analyzes the complexity of text and voice techniques to deliver translated content …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 2, 2024 · pp. 13–21 Read article
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Development of Polymer-Based Sensors for Speech Emotion Recognition
Abstract: Traditional SER research often utilizes microphones with polymer components like Diaphragms and Membranes. Within some microphone designs, polymer membranes which plays a crucial role in converting sound pressure into electrical signals. The paper highlights the application (speech emotion recognition) and have tried to find polymer-based sensors. This work further delves deeper, investigating the performance of the CatBoost algorithm for emotion recognition in voice assistants designed for Indian languages. The research …
Published in Journal of Polymer & Composites · Vol. 12, Issue 5, 2024 · pp. 268–274 Read article
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AI Based Mock Interview Evaluator
Abstract: AI-based mock interview platform that acts as a bridge between real interviews and preparation. The system evaluates users based on emotions, confidence, and knowledge. Emotions are analyzed using a deep learning CNN algorithm to classify facial expressions. Confidence is also a main feature in interview which is assessed through speech recognition using natural language processing. Knowledge assessment involves taking online tests and answering along with the description. This platform aims …
Published in Journal of Mechatronics and Automation · Vol. 11, Issue 2, 2024 · pp. 1–5 Read article
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VERONICA: AI-Driven Edge System for Comprehensive Bike Safety and Assistance Through Multi-Source Data Fusion
Abstract: Road safety for bike riders remains a significant concern, with accident rates highlighting the need for advanced solutions to ensure rider protection and awareness. This paper presents “VERONICA: AI-Driven Edge System for Comprehensive Bike Safety and Assistance Through Multi-Source Data Fusion”, a voice-activated, continuously operating assistance system designed to provide real-time, intelligent solutions for various riding scenarios. VERONICA integrates accident detection, low-traffic route navigation, traction control advisories, and weather updates …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 14, Issue 1, 2025 · pp. 09–17 Read article
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Optimized Text Extraction and E-Repository Development of Hindi and Punjabi Documents Using OCR and NLP Techniques
Abstract: Increase in digitalization of content in the form of text content necessitates powerful document and text extraction systems, particularly for Indian languages such as Hindi and Punjabi. The existing Optical Character Recognition (OCR) solutions support major scripts such as English, leaving a research opportunity for effective recognition of Devanagari and Gurmukhi scripts. This study recommends a modified text extraction algorithm based on Tesseract OCR, accompanied by preprocessing steps of conversion …
Published in Journal of Web Engineering & Technology · Vol. 12, Issue 3, 2025 · pp. 35–43 Read article