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51 articles for “Object Recognition”
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Oral Self-examination: An Approach for Early Recognition of Oral Cancer Among Factory Workers: An Experimental Study
Abstract: Background: Cancer is a worldwide concern and ranks among the most dreaded illnesses across the globe. Oral cancers are one common cancer among all cancers. Objectives: To measure the existing knowledge concerning oral self-examination for timely recognition of oral cancer among factory workers and to develop and administer a planned health education programme of oral self-examination for early recognition of oral cancer among factory workers. 40 factory workers were selected …
Published in International Journal of Oncological Nursing and Practices · Vol. 1, Issue 2, 2023 · pp. 22–26 Read article
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Discourse of Self and Other in Landscape by Harold Pinter
Abstract: This paper explores Harold Pinter’s Landscape as a pivotal representation of the complex dynamics between the subjective self and social reality. It investigates how the characters' introspection blurs the line between objective and subjective truths, highlighting their disillusionment with present-day existence and their reliance on past memories for solace. Through a dialectic discourse, Pinter’s characters reconstruct their identities and relationships, presenting fragmented versions of truth that reveal the unreliability of …
Published in Emerging Trends in Languages · Vol. 2, Issue 1, 2025 · pp. 10–17 Read article
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AI-Enhanced Interpretation of Cardiac Troponins: Toward Predictive Precision in Myocardial Injury
Abstract: Background: Cardiac troponins (cTn) represent the gold standard biomarkers for myocardial injury detection, yet their interpretation remains challenging due to various confounding factors and clinical contexts. Artificial intelligence (AI) technologies provide remarkable possibilities to improve the interpretation of troponin levels by utilizing pattern recognition, predictive modeling, and clinical decision-making support. Objective: This review examines the current state and future potential of AI-enhanced cardiac troponin interpretation, focusing on machine learning applications, …
Published in Research and Reviews: A Journal of Medicine · Vol. 15, Issue 3, 2025 · pp. 1–9 Read article
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Navigating Risk-Based Approaches in Quality Assurance: Strategies, Implementation, and Impact
Abstract: This review investigates the implementation of a risk-based approach within Quality Management Systems (QMS) as stipulated by ISO 9001:2015 regulations. It scrutinizes the challenges organizations encounter when transitioning to ISO 9001-2015 requirements, particularly focusing on the alignment of conceptual frameworks and processes among stakeholders. A key objective of this review is to propose a refined definition of "quality risk" and "risk-based thinking in QMS" to address the idiosyncratic characteristics of …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 11, Issue 2, 2024 Read article
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Entropy, Symmetry, and Data Fusion: Emerging Methods in Multi-Objective Decision- Making and Smart Systems
Abstract: In the era of intelligent technologies and data-driven systems, multi-objective decision-making (MODM) has become an essential aspect of managing complex environments such as smart cities, autonomous systems, and cyber-physical networks. As decision-making scenarios become increasingly dynamic and uncertain, there is a growing need for advanced methodologies that can handle diverse objectives, conflicting constraints, and incomplete information. This review highlights the emerging role of entropy, symmetry, and data fusion as foundational …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 2, 2025 · pp. 44–49 Read article
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Avian Echoes: Convolutional Neural Network for Bird Vocalization Detection
Abstract: Bird species identification is a complex task within ornithology that demands advanced technological solutions. This research presents an approach leveraging Convolutional Neural Networks (CNNs) for bird species recognition based on identification of bird sound, each employing unique datasets and methodologies. The objective involves a two-stage identification process, beginning with the construction of an ideal dataset. The crucial step involves converting 1D audio waveforms to 2D spectrograms, enhancing CNNs' ability to …
Published in Journal of Aerospace Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 26–37 Read article
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Facial Biometrics Driven Attendance Automation Solution Using LBPH Algorithm
Abstract: In today's educational landscape, managing attendance remains a central administrative task, often conducted manually on paper, consuming valuable time for educators. This project proposes a solution utilizing facial recognition technology to streamline the attendance process, thereby saving time and maintaining accurate student records. The objective is to develop an automated attendance system that is minimally intrusive, cost-effective, and highly efficient, leveraging computer vision techniques and algorithms like local binary patterns …
Published in Journal of Open Source Developments · Vol. 11, Issue 1, 2024 · pp. 27–35 Read article
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Conceptual Framework and Hypothesis Development for Green Supply Chain Practices
Abstract: In recent decades, sustainability has gained significant attention. Green Supply Chain Management (GSCM) ensures that corporate and governmental initiatives effectively make operations more environmentally friendly, increase market share, enhance brand recognition, and boost profitability. Sustainable or "green" supply chain management integrates both financial and environmental objectives into the strategy for managing supply chain operations. This integration helps reduce carbon footprints while improving profitability and financial returns. GSCM encompasses various aspects, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 64–78 Read article
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Advanced Helmet Recognition System with Integrated Number Plate Detection for Enhanced Traffic Monitoring Using Deep Learning
Abstract: This study focuses on the crucial problem of non-adherence to traffic regulations, particularly with the compulsory use of helmets by motorcyclists. Motorcycle accidents have a greater mortality rate compared to other types of accidents, indicating a need for a more effective enforcement strategy. Current procedures depend on traditional techniques where traffic officers manually observe traffic rule infractions through patrols and monitoring CCTVs, requiring substantial labor and time resources. The inherent …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 1, 2024 · pp. 9–18 Read article
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Assessing the Performance of DL Methods in Handwritten Digit Recognition
Abstract: Handwritten digit recognition is a computer vision task that involves the automatic identification and classification of hand-written digits. The objective is to develop models capable of accurately recognizing and distinguishing digits handwritten by humans. With the development of machine learning and deep learning techniques, this field has advanced remarkably. The convolutional neural network (CNN) is the most often used technique for this purpose. By utilizing CNN, the model can learn …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 1, 2023 · pp. 25–32 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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Automated Car License Plate Detection and Recognition Using Deep Learning
Abstract: The use of automated license plate detection and recognition (ALPR) systems to automate processes such as number plate detection is gaining popularity in traffic control, security, and law enforcement. This research focuses on achieving more accurate and efficient detection and recognition of number plates by leveraging deep learning techniques. The systems outlined in this study aim to improve the effectiveness of ALPR systems using advanced convolutional neural networks (CNNs) and …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 23–29 Read article
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AI-Driven Micro-Expression Recognition for Early Mental Health Disorder
Abstract: Mental health conditions like anxiety and depression are often undiagnosed because the usual diagnostic methods based on basic regular instruments like questionnaires and clinical interviews have some limitations in them. They are not objective often and may not catch the initial signs of psychological distress. Micro-expressions have become valid measures of repressed or unconscious emotions and can provide greater insight into someone's mental condition. Also, identification and interpretation of these …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 3, 2025 · pp. 40–49 Read article
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Real-time Voice-over Translation
Abstract: The real-time voice-over translation project stands as a pioneering endeavor poised to reshape the landscape of cross-cultural communication. In response to the escalating demand for fluid interaction amidst linguistic diversity, this initiative sets out to engineer a transformative solution. Its core objective lies in the seamless mediation of language barriers during real-time exchanges. Through the fusion of cutting-edge speech recognition and machine translation technologies, the project endeavors to fabricate a …
Published in International Journal of Computer Science Languages · Vol. 2, Issue 1, 2024 · pp. 24–32 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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OpenCV, AI, and Haar Cascade File: A Review
Abstract: Real-time image processing applications using OpenCV encompass a diverse and crucial array of tasks in modern technology. OpenCV's robust capabilities enable the implementation of object detection and tracking, which are vital for surveillance systems to monitor and analyze activities in real time. In the realm of security, face recognition technology, powered by OpenCV, provides accurate and efficient identification and authentication, enhancing safety measures. Gesture recognition, another significant application, facilitates intuitive …
Published in Journal of Open Source Developments · Vol. 11, Issue 2, 2024 · pp. 39–46 Read article
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AI-Powered Emotion Recognition in Dog
Abstract: Understanding animal emotions is important for improving veterinary care, human animal interaction, and overall pet well-being. Inspired by previous research that utilized a modified EfficientNetB5 model for emotion classification in cats and dogs, our study builds upon this foundation with a focus on real-time emotion recognition in dogs. While earlier approaches achieved high accuracy using Dense Residual and Squeeze-and-Excitation blocks, they often lacked real-time applicability and were not optimized for …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 · pp. 20–32 Read article
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Acoustic Sensing for City Flow: Quasi-Supervised Recognition of Sirens and Traffic for Urban Mobility Intelligence
Abstract: This paper frames environmental audio as a mobility telemetry source, extending a benchmark urban-sound corpus with transportation-critical classes—ambulance, firetruck, police, and traffic—and training spectrogram-based models under a quasi-supervised regime to support real-time city operations; leveraging 10-fold protocols, class-weighted objectives, and audiospecific augmentations (time stretch, pitch shift, SpecAugment, PatchAugment), the system benchmarks multiple CNN backbones combined with self-supervised learning paradigms enable the extraction of rich, discriminative acoustic representations, achieving strong multi-class …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 42–50 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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Real-Time Object Detection and Tracking in Traffic Surveillance: Implementing Algorithms That Can Process Video Streams for Immediate Traffic Monitoring
Abstract: The rapid growth in urban development and traffic congestion calls for adopting high standards of traffic surveillance systems for monitoring. This paper reviews the current advancement and future trends of real-time object detection and tracking technology and its implications for traffic surveillance. Conventional approaches to traffic monitoring can provide more or less accurate data, but they are not easily scalable and cannot cope with rapidly changing conditions typical within urban …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 18–39 Read article