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13 articles for “CNN and OpenCV”
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Facial Emotion Recognition Using CNN and OpenCV: A Review
Abstract: Emotion Recognition Using a Facial Feature Recognition is a prominent area of study in the world of Human Computer Interaction (HCI). Humans may express a wide range of emotions and moods through facial movements and body language. In this project, in order to detect the live emotions from the human facial gesture, we will be using an algorithm that allows the computer to automatically detect the facial recognition of human …
Published in Journal of Open Source Developments · Vol. 10, Issue 1, 2023 · pp. 1–9 Read article
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Fake User Identification and Duplication Detection Using Aadhaar Card
Abstract: Various universities are facing several issues concerning students' fake enrollment, duplication, and authentication of student details. Here we are providing solutions to improve student enrollment process for various exams by using convolutional neural networks (CNN) and OpenCV (Open-Source Computer Vision Library). A solution to the existing system must be versatile and precise. If the project aims to be used for large-scale deployments, then it must be adaptable and accurate in …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 10, Issue 1, 2023 · pp. 13–19 Read article
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Identification of Papaya Fruit Ripening Process Using AI
Abstract: Identifying the ripening process of papaya fruit using artificial intelligence involves employing machine learning algorithms to analyze various features such as color changes, texture alterations and chemical compositions. This model is capable of analyzing visual cues to determine the stage of ripeness. The dataset compares images of papaya at various ripening stages, and our AI model demonstrated high accuracy in classifying these stages. Employing machine learning algorithms and image processing …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 13, Issue 2, 2024 · pp. 23–30 Read article
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Plants Disease Detection Using TensorFlow and OpenCV
Abstract: Growing healthy and productive crops is crucial in the global battle for food security. To minimize crop losses and apply timely control measures, early and precise diagnosis of plant diseases is essential. Conventional illness detection techniques are subjective, labor-intensive, and complicated; they frequently rely on eye inspection. The TensorFlow and OpenCV libraries are used in this study to explore the use of Convolutional Neural Networks (CNNs) for plant disease discovery. …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 1, 2024 · pp. 31–38 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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A Comparative Study on Emotion and Gender Prediction using OpenCV Library and Deep Learning
Abstract: AbstractIn this paper, we are going to study and develop a convolutional neural network (CNN) using EmoPy python Library for training our dataset, which performs human facial recognition as well as their gender prediction with real-time emotions. This model will work with OpenCV, Keras 2.3.1 and EmoPy. A fully connected layer of convolutional neural network which identifies the gender as well as the art of emotion of the human for …
Published in Journal of Advancements in Robotics · Vol. 7, Issue 3, 2020 · pp. 20–25 Read article
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Remote Healthcare Diabetic Retinopathy Detection Using Deep Learning
Abstract: High blood glucose levels are a hallmark of diabetes mellitus (DM), a metabolic disease. This can give rise to a range of complications, with Diabetic Retinopathy (DR) being among them. DR can impair vision and, if not addressed, may lead to a loss of eyesight. Symptoms include aberrant blood vessels, fluid leaks, exudates, haemorrhages, and retinal microaneurysms. With the advancement of technology, medical imaging has become one of the most …
Published in Journal of Open Source Developments · Vol. 10, Issue 2, 2023 · pp. 42–47 Read article
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Real-time Sign Language Detection Using Computer Vision and Machine Learning Techniques
Abstract: Communication plays an important role in our day-to-day lives as it assists people in sharing, and connecting to each other. Despite knowing the significance of the same, some deaf-mute pupils who are not able to communicate freely. These groups of people use sign language for sharing their thoughts. It could be a tough task to understand sign language for a group of humans who are not deaf-mute. We developed a …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 10, Issue 1, 2023 · pp. 10–19 Read article
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ASL Mobile Translator with CNN Algorithm
Abstract: There are around 63 million people in India with speech and hearing disabilities, and the number goes all the way up to 300 million across the world. All of them face issues in their day-to-day life as they can only have conversations with gestures. American Sign Language (ASL) mobile translator with convolutional neural network (CNN) algorithm is an easy-to-use mobile application, which uses complex images and video recognizing models built …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 1, Issue 2, 2023 · pp. 31–38 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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Interpretable Skin Cancer Detection via Optimized CNN Models for Smart Healthcare Solutions
Abstract: Skin cancer is a common and potentially life-threatening condition, highlighting the importance of reliable and efficient diagnostic techniques. Recently, convolutional neural networks (CNNs) have demonstrated significant potential in automating the classification of skin cancer using thermoscopic images. Despite these advancements, the lack of interpretability in these models poses a barrier to their widespread use in clinical settings. In this study, we propose an interpretable CNN architecture optimized for skin cancer …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 41–45 Read article
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Object Detection Using Deep Learning Algorithm
Abstract: Object detection is a computer technology related to computer vision and image processing that deals with detecting images of semantic objects of a certain class (for example cars, buildings, etc.) in digital images and videos. To detect objects, there are many algorithms available, in this paper YOLO algorithm is explored for detection of objects on real-time data. You Only Look Once (YOLO) is a state-of-the-art real time object detection system …
Published in Journal of Control & Instrumentation · Vol. 12, Issue 2, 2021 · pp. 1–13 Read article
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Attendance System Based on Facial Recognition
Abstract: Attendance management is a fundamental aspect of educational institutions and workplaces, ensuring accountability, discipline, and operational efficiency. Traditional methods, such as manual roll calls, RFID cards, and fingerprint scanners, are often time-consuming, error-prone, and susceptible to fraud. This research presents an automated attendance management system utilizing face recognition technology to address these challenges effectively. The proposed system employs OpenCV for real-time image processing, the face recognition library for accurate facial …
Published in International Journal of Electronics Automation · Vol. 3, Issue 1, 2025 · pp. 28–34 Read article