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129 articles for “Feature recognition”
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Comparative Analysis Between Librosa and OpenSMILE
Abstract: This research work focuses on comparative study of Librosa, a python-based library, and openSMILE, a C++ toolkit, with python bindings used in audio speech analysis. Librosa is ideal for beginners due to its simple structure and flexibility with strong integration with machine learning frameworks like TensorFlow and PyTorch. On the other hand, OpenSMILE is ideal for speech-centric tasks like speech-emotion recognition or paralinguistic studies, offering a wide range of pre-defined …
Published in Journal of Open Source Developments · Vol. 12, Issue 3, 2025 · pp. 06–10 Read article
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Sentiment Analysis Using Emojis
Abstract: Sentiment analysis is a fast-growing research part in NLP (Natural Language Processing). It is fully focused on categorizing customer’s opinion about a particular product, blogs or comments etc. Public opinion has a significant impact on people's desire to contact with businesses, as well as overall brand perception. According to a Podium research, 93% of buyers believe online reviews affect their shopping decisions. Users may not give you another chance after …
Published in Journal of Computer Technology & Applications · Vol. 13, Issue 1, 2022 · pp. 43–46 Read article
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AI-Based Criminal Identification System A Breakthrough Approach
Abstract: Identifying and locating a perpetrator is a time-consuming and difficult process. The perpetrators are growing more skilled, leaving no biological evidence or fingerprint impressions at the crime scene. Using cutting-edge face recognition technology is a quick and easy solution. Through the use of linear programming, this research presents an innovative approach to classifying all face tracks collectively. In addition to the following, it incorporates: a novel method for extracting more …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 2, Issue 1, 2024 · pp. 1–14 Read article
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Virtual Method to Predict Dental Disease
Abstract: The integration of technology and medicine in the healthcare domain has led to the emergence of inventive strategies to improve patient care and diagnostics. One such groundbreaking methodology is the utilization of Convolutional Neural Networks (CNNs) within the domain of deep learning, particularly for image recognition and processing tasks. In this paper, we propose a novel approach to image recognition that employs state-of-the-art deep learning algorithms to create a user-friendly …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 8–15 Read article
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Numerals Recognition for Urdu Script
Abstract: Optical Character Recognition is a difficult task due to the complexities of the script and varying location of the character in the image. Characters of Urdu script-based languages are even more difficult to recognize but they have not received much attention in spite of the fact that Urdu ranks sixth in the top 10 most-spoken primary languages (181 million people). The problem of numeral recognition in Urdu is due to …
Published in Current Trends in Signal Processing · Vol. 1, Issue 1-3, 2025 · pp. 11–16 Read article
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Efficient Masked Face Recognition Methods using Deep Learning
Abstract: Covid-19 questioned not only people's health but alsoconventional scientific systems. Due to face masks that were made mandatory to wear, the existing cognitive systems failed to perform in real-time scenarios. The demand to develop face recognition systems that detect people even when they wore masks was naturallyhigh. Deep learning techniques help to solve this problem, working efficiently in detecting user face features and comparing them with a known image database. …
Published in Journal of Instrumentation Technology & Innovations · Vol. 13, Issue 2, 2023 · pp. 1–10 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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Automated System for Attendance Tracking and Management Using Face Recognition
Abstract: A camera is used by an attendance tracking system that uses facial recognition to snap photos of people. After that, a computer program analyzes these images and uses facial feature analysis to identify specific individuals. Subsequently, the system can ascertain whether or not the identified individuals are present, by comparing the identified individuals to a database that already has information about known individuals. This technology can be used to expedite …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 2, 2024 · pp. 1–12 Read article
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AI based Assistive glasses for visually impaired persons
Abstract: There been a lot of change in tools for assisting visually impaired persons from simple analog tools to digital sensor-based devices. In this paper we have designed an AI- based smart assistive glass which can detect objects, read text their nature, distance and give feedback through audio output in real time. This system stores visual data and with use of object recognition it analyzes surroundings.Besides,VL53L0X TOF mea- sures accurate distance …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 2, 2026 · pp. 22–29 Read article
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License Plate Detection using CNN
Abstract: Tag recognition is a picture preparing innovation used to distinguish vehicles by their tags. This advancement is used in various security and traffic applications. Deep learning employs complex mechanisms to extract features from samples This paper proposes a system trained using the MobileNetV2 convolutional neural network (CNN) model to detect the characters and digits from vehicle license plates. Our approach is highly influenced by the recent advancements made in the …
Published in Journal Of Network security · Vol. 9, Issue 2, 2021 · pp. 21–27 Read article
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AGRISMART: Crop and Soil Management System
Abstract: Agriculture has played a crucial role in developing countries where the majority of the rural population relies on it for their livelihoods. A finer-grade crop classification has become crucial in the context of precision agriculture. In recent years, the volume of open image data has grown significantly. This can be used in combination with machine learning techniques to classify crop types in the agricultural industry. The proposed crop species recognition …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 3, 2025 · pp. 50–55 Read article
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Fake Currency Detection Using Convolutional Neural Networks
Abstract: In today’s world, due to increasing technology like scanning, color printing, and duplicating, the identification of bogus notes by the human eye is almost getting impossible. Knowingly or unknowingly, due to the usage of bogus currency notes, the Indian economy is also being impacted badly. Hence, the identification of bogus currency notes is really important. This paper deals with regard to identifying whether the given sample of the currency note …
Published in Journal of Electronic Design Technology · Vol. 14, Issue 2, 2023 · pp. 9–17 Read article
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Evolving Perspectives: Innovations in Object Detection and Identification
Abstract: One of the most important developments in computer vision has been the creation of object detection and identification systems, which have allowed robots to perceive and understand visual data similarly to humans. These systems locate each object by drawing a bounding box around it, in addition to detecting and classifying every object in an image or video. This study suggests a novel method for item identification and detection that makes …
Published in Trends in Opto-electro & Optical Communication · Vol. 13, Issue 3, 2023 · pp. 23–27 Read article
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Mood Mate: A Solid-State Edge-AI System for Real-Time Facial Emotion Recognition
Abstract: Recent progress in solid-state electronics and embedded vision systems has enabled real-time emotion-aware applications at the edge. This paper presents MoodMate, a solid-state edge-AI framework for real-time facial emotion recognition using camera-based sensing and embedded processing. The proposed system integrates a solid-state image sensor with an AI- driven emotion classification pipeline optimized for low-latency and resource-constrained environments. Intelligent, emotion-aware apps can now be deployed right at the network edge thanks …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 24–30 Read article
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Advancements in Handwriting Recognition: A Deep Learning Approach
Abstract: This article provides detailed information about handwriting text recognition. Some human characteristics are unique to the individual. Writing is one of the scientifically proven habits that is different for everyone. Handwriting Text Recognition (HTR) is responsible for identifying written characters and converting them into digital text. HTR is an intensively researched area, but improvements can still be made in accuracy and efficiency. Digitization of manuscripts is very useful in today's …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 28–34 Read article
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Age, Gender And Emotion Detection
Abstract: The main reason is the development of a method to automatically estimate the age and gender of the human face. It continues to play an important role in computer vision and pattern recognition. In addition to age determination, facial emotion recognition also plays an important role in computer vision. Nonverbal communication methods such as facial expressions, eye movements, and gestures are used in many human-computer interaction applications. Much research has …
Published in Recent Trends in Sensor Research & Technology · Vol. 9, Issue 1, 2022 · pp. 1–6 Read article
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Revolutionary Cursor Control Systems: Enhancing Human-Computer Interaction
Abstract: This project delves into leveraging artificial intelligence within virtual mouse systems to elevate human-computer interaction. The main objective is to improve user experience, increase efficiency, and introduce new ways of interaction. Employing artificial intelligence techniques such as computer vision, gesture recognition and speech recognition, the virtual mouse system adeptly tracks hand movements, interprets voice commands, recognizes gestures, and processes user inputs for seamless interactions. Tailoring features for design, gaming, accessibility, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 45–52 Read article
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Robust Classification of Traffic Signs Using Relief Feature Reduction Technique
Abstract: Ensuring driver safety amidst the rapid growth of global population and vehicular density continues to be a paramount challenge for transportation authorities and governments worldwide. With the rise of smart mobility solutions and autonomous driving technologies, the ability to detect, classify, and respond to traffic signs accurately has become critically important, especially under diverse and adverse environmental conditions such as rain, fog, or poor lighting. Reliable traffic sign recognition not …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 30–37 Read article
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Sustainable Cotton Crop Productivity through Precision Weed Detection: A Deep Learning-Based Approach with UAV Integration
Abstract: Weeds present a major challenge to crop productivity by competing with crops for vital resources, including water, sunlight, and nutrients, often resulting in significant yield reductions. On a global scale, weeds are responsible for approximately 13.2% of annual crop losses, a quantity sufficient to feed nearly one billion people. These invasive plants disrupt agricultural systems and adversely impact crop yields. Given their uneven distribution in fields, ground or aerial robots …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 19–26 Read article
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Medically Important Hemiptera: Bed Bugs and Kissing Bugs in Human Health.
Abstract: Bed bugs (family Cimicidae) and kissing bugs (subfamily Triatominae) are hematophagous Hemiptera of major medical importance, yet they differ markedly in their public health impact. Bed bugs have resurged globally over the past three decades, with infestations reported from homes, multi-unit housing, hotels, transportation, and healthcare facilities in both high and low-income settings. They are not established biological vectors of human pathogens, but their bites cause pruritic papules, urticarial, and …
Published in International Journal of Insects · Vol. 3, Issue 1, 2026 · pp. 41–49 Read article