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129 articles for “Feature recognition”
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Identification of English Dialects and Emotions using Spectral and Prosodic Features of Speech Signal Processing
Abstract: AbstractIn this paper, the authors have explored speech features to identify English dialects and emotions. A dialect is any distinguishable variety of a language spoken by a group of people. Emotions provide naturalness to speech. Speech database considered for dialect identification task consists of spontaneous speech spoken by male and female speakers. The emotions considered in this study are anger, disgust, fear, happy, neutral and sad. Prosodic and spectral features …
Published in Journal of Computer Technology & Applications · Vol. 4, Issue 2, 2013 · pp. 10–17 Read article
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Procedure for Conventional Facial Emotion Detection Algorithms Based on Machine Learning
Abstract: Researchers in psychology, computer science, linguistics, neurology, and allied fields have become more interested in a human-computer interface system for autonomous face recognition or facial expression recognition. This study has recommended an Automatic Facial Expression Recognition System (AFERS). The proposed methodology consists of face detection, feature extraction, and facial expression identification processes. The initial phases of the face detection procedure include skin color identification using the YCbCr color model, illumination …
Published in International Journal of Electronics Automation · Vol. 1, Issue 1, 2023 · pp. 07–13 Read article
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AI-Driven Handwriting Identification and Verification Using Textural Features
Abstract: The last few decades have seen handwriting recognition and verification earn their mark in areas like forensics, healthcare, education, and digital security. This study delves into the role of artificial intelligence (AI), machine learning (ML), and deep learning techniques in handwriting analysis. It highlights the extraction of textural features as a precursor to identifying narrows between original handwriting and its forgery, whereby a few distinctive patterns such as stroke width, …
Published in International Journal of Electronics Automation · Vol. 3, Issue 1, 2025 · pp. 35–44 Read article
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Smart Glasses Using Ultrasonic Sensor and AI for Blind Person
Abstract: Smart glasses has received considerable attention recently from people around the world. This research paper introduces a pioneering project, 'Smart Glasses Using AI and Ultrasonic Sensor,' aimed at revolutionizing the assistive technology landscape for visually impaired individuals. The project seamlessly integrates advanced hardware, including Raspberry Pi and Node MCU, with an array of sensors and state-of-the-art machine learning techniques, notably the YOLOv5 model. This paper presents a new paradigm in …
Published in Recent Trends in Sensor Research & Technology · Vol. 11, Issue 2, 2024 · pp. 1–9 Read article
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An Approach to Image Recognition on the Basis of Plant Diseases Ontology
Abstract: AbstractOntology engineering for the plant science is supposed to contribute on the basis of plants traits that determine phenotypic expression in a given environment. Plants play a very important role in the ecological balance and daily necessities in the life. Due to environmental or other causes many of the plants become damaged and hence the investigation of the plant recognition on the basis of diseases is a major research area …
Published in Journal of Computer Technology & Applications · Vol. 6, Issue 3, 2015 · pp. 1–9 Read article
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Artificial Intelligence in Image Recognition: Context of Machine Vision
Abstract: The machine learning discipline is as old as decades, but some problems such as image recognition, location detection, image classification, image generation, speech recognition, and natural language processing cannot be solved. Image classification studies are another basic, most classic and essential line of research in deep learning. Computer intelligent recognition of the images technology has enabled a gradual reaction (updating) to foreign measurement trends, which promotes advancement of different areas …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 01–06 Read article
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Discrete Hidden Markov Model based Face Recognition System Introducing Sustainability of Uneven Lighting Distortion
Abstract: The aim of this work is to enhance the performance of appearance based face recognition system to remove the uneven lighting effect which is generally occurred in natural environment. Active Shape Model has been used to detect the facial shape and contrast based edge detection technique has been applied to reduce the uneven lighting problem. Linear Discriminant Analysis has been used to reduce the dimension of the facial feature vector. …
Published in Trends in Electrical Engineering · Vol. 4, Issue 1, 2014 · pp. 9–16 Read article
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CNN-BILSTM Architectures for Handwritten Signature Verification: Insights and Innovations
Abstract: Verifying handwritten signatures is essential for identity authentication to guard against fraud and guarantee security across a range of platforms. The approaches and developments in handwritten signature verification are examined in this review, with an emphasis on both offline and online techniques. While online methods use dynamic information like stroke order and speed, collected by specialized devices, offline verification uses scanned photographs of signatures. Even if technology is moving toward …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 2, 2025 · pp. 43–50 Read article
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Dimensionality Reduction using Eigenfaces and Fisherfaces for Face Recognition Applications using Kernel LMS Algorithm
Abstract: AbstractFace recognition is an intricate numerical technology in computer systems that can support recognition of human faces using methods such as principal component analysis (PCA), linear discriminant analysis (LDA), etc. by comparing the given facial uniqueness with the already available face database. PCA and LDA are classical feature extraction and data representation techniques used in face recognition algorithm involving unsupervised statistical methods. The 2-D facial image can be transformed into …
Published in Journal of Computer Technology & Applications · Vol. 6, Issue 2, 2015 · pp. 29–55 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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Compact Autonomous Multipurpose IoT BOT
Abstract: AbstractInternet of things (IoT) is widely used in interconnection of physical and other embedded devices, which enables the objects to exchange data. Robotics is the technology which is used to carry out complex series of actions either automatically or command based, guided by an embedded system within it. The proposed work is an integration of IoT with robotics for home automation. First, when the user enters into the house, robot …
Published in Journal of Instrumentation Technology & Innovations · Vol. 8, Issue 1, 2018 · pp. 27–33 Read article
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Digital Resurrection: Restoring Fragile Documents with OCR
Abstract: In creating a typical Optical Character Recognition (OCR) system, several steps are involved, such as preprocessing, segmentation, feature extraction, and classification. Preprocessing, which is a particularly interesting and challenging aspect of Document Analysis and Recognition (DAR), deals with converting scanned or photographed images containing machine-printed or handwritten text, including numbers, letters, and symbols, into a format that the system can understand. Segmentation is a crucial task in any OCR system, …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 2, 2024 · pp. 29–35 Read article
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Recognition of Unconstrained Handwritten Digits Using Feedforward MLP and Projection Profile
Abstract: AbstractThis paper presents a new approach to off-line handwritten numeral recognition using feedforward MLP and projection profile. Different writers have variations in their handwriting since each writer possesses own writing speed, own styles, sizes or positions for numeral or text. Recognition of handwritten numerals poses serious problems because of high variability in numeral shapes written by individuals. The performance of character recognition system depends heavily on what kind of features …
Published in Journal of Communication Engineering & Systems · Vol. 5, Issue 2, 2015 · pp. 15–20 Read article
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A Deep Survey on Techniques Used to Recognize Locust Based on CNN
Abstract: The major threat in agriculture is insect pests and crop disease. Outbreaks and upsurges of insects can cause huge loss to crop production. Locusts are crop devouring pests found in many parts of the world. Recognition of locusts in early stage helps to prevent the spread of locusts by taking appropriate counter-measures and biological control methods. Initially, locusts were classified and recognized manually which is time consuming and requires taxonomic …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 1, 2021 · pp. 1–8 Read article
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Comparative Analysis of MCNN and RCNN for Speech Emotion Recognition Using Gender Information
Abstract: Speech emotion recognition is a speech processing task and a computer-based approach designed to identify and classify the emotions conveyed in audio signals. The aim of this system is to evaluate a speaker's emotional state, such as happiness, anger, sadness, or frustration, by analyzing their speech patterns, which include prosodic features like pitch, frequency, and rhythm. Speech emotion recognition is used in various real-life scenarios that include Customer Service, Healthcare, …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 1, 2025 · pp. 1–10 Read article
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Arduino Empowered: Smart Glove Review and Analysis
Abstract: In recent years, there has been a growing interest in wearable technology, particularly in the realm of human-computer interaction (HCI). Smart gloves, equipped with various sensors and actuators, have emerged as a promising interface for facilitating seamless interaction between humans and digital devices. This paper presents the development of Arduino-based smart gloves designed to augment conventional HCI methods by incorporating gesture recognition and tactile feedback capabilities. The smart gloves feature …
Published in Journal of Microcontroller Engineering and Applications · Vol. 11, Issue 1, 2024 Read article
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Evaluation of composite material based on different phases of Face recognition System
Abstract: Composite materials can indeed play a crucial role in various phases of a face recognition system, offering advantages such as lightweight construction, durability, and tailored mechanical properties. Let's explore how composite materials can be utilized in different phases of a face recognition system. A composite material based different phases of Face recognitions System is software that recognizes or verifies a person based on a digital image or a frame from …
Published in Journal of Polymer & Composites · Vol. 12, Issue 2, 2024 · pp. 195–204 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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Effective FPGA Implementation of Comb Filters to Improve Perception of Sensorineural Hearing Impaired
Abstract: AbstractIn this paper, effective method for implementation of comb filter on FPGA platform has been proposed. This work is intended for hearing aid to be used for people suffering from sensorineural hearing loss. The algorithmic implementation on FPGA is intricate during the design process. Here we propose effective and simplified approach for implementation of comb filter with 512 coefficients using Spartan-6 FPGA for dichotic presentation. The design of comb filter …
Published in Current Trends in Signal Processing · Vol. 7, Issue 3, 2017 · pp. 15–29 Read article
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Lip Reading: Transforming Speech to Text
Abstract: Lip reading, the ability to interpret spoken language by observing lip movements, is a valuable skill that can aid in various applications, particularly in enhancing speech recognition systems. This project explores the implementation of a deep learning-based lip-reading model to improve the accuracy and robustness of speech recognition in challenging environments, such as noisy or audio-limited settings. The proposed lip-reading system leverages Convolutional Neural Networks (CNNs) and Recurrent Neural Networks …
Published in Current Trends in Signal Processing · Vol. 14, Issue 1, 2024 · pp. 23–33 Read article