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36 articles for “Key frames extraction”
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Performance Evaluation of PCA Based Back Propagation over PCA Based Euclidian Distance for Video Images
Abstract: Key frame selection aims at reducing amount of data and retrieve information desired from a video. Video summarization aims at reducing the amount of data in order to retrieve information from a video. In this paper, we present an innovative approach for key frame selection; and a face detection and recognition from video sequence. For face detection from video, first we select the key frames and then detect multiple faces …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 1, 2016 · pp. 24–31 Read article
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Visual Duplicates in Video using Content based Analysis
Abstract: This paper proposes a technique to detect visual duplicates in video using content-based analysis for analyzing duplicate videos in the database. Content-based analysis refers to analysis of digital media on the basis of features extracted from its contents. The proposed algorithm uses key frames, extracts spatial features and stores them in their respective feature vector. Feature vector stores the features extracted from key frame in numerical form. It then compares …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 1, Issue 1, 2014 · pp. 6–11 Read article
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Application-Driven Rule-Based Framework for Lubrication Failure Modes in Industrial Systems
Abstract: Modern lubricants increasingly rely on polymer-based composites, integrating synthetic base oils, polymer thickeners and solid additives like MoS₂ and PTFE for high-performance applications. These formulations not only enhance thermal and mechanical stability but also enable low-friction operation across diverse industrial conditions. Lubrication-related failures represent a critical cause of unplanned downtime and reduced reliability in industrial machinery. This paper presents an application-driven, rule-based framework designed to assess and mitigate lubrication failure …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 522–531 Read article
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Semantic Similarity Framework for Automatic Hallucination Detection in Large Language Models
Abstract: Large Language Models can generate fluent, contextually appropriate text across a range of NLP tasks, but they frequently produce outputs that are factually wrong while sounding confident and plausible. This problem, referred to as hallucination, poses serious risks in domains where accuracy matters. We propose a post-processing framework that detects hallucinated responses by comparing them against verified reference text using sentence embeddings. The system computes cosine similarity between the response …
Published in Emerging Trends in Languages · Vol. 3, Issue 2, 2026 · pp. 16–22 Read article
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Video Watermark for Text Data Using QR Code
Abstract: In the current era, data security is most important and so is copyright protection. By using this project, the user can secure his data, logo etc. We are incorporating a digital video watermark into QR Codes for text data. This technique is used for data hiding into video. This technique can be classified as either spatial or frequency domain. Some video watermarking issues are addressed in video watermarking. This project …
Published in Journal of Operating Systems Development & Trends · Vol. 9, Issue 1, 2022 · pp. 28–34 Read article
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Facial Recognition System Utilizing Real-time Deep Learning Techniques
Abstract: This research introduces an openly accessible deep learning-based framework designed for facial recognition. The system encompasses five key stages: face segmentation, detection of facial features, face alignment, embedding, and classification. Deep learning methods are employed for the extraction of fiducial points and embedding within the system. For the classification task, a Support Vector Machine (SVM) is utilized due to its efficiency in both training and inference phases. Notably, the system …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 1, 2024 · pp. 14–20 Read article
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A Conceptual Framework for AI-Integrated Metabolomics in Predictive Health Systems for Resource-Constrained Environments
Abstract: The increasing prevalence of non-communicable diseases (NCDs) continues to place a significant strain on healthcare systems, particularly in low- and middle-income regions where access to early diagnostic infrastructure is limited. Conventional healthcare approaches remain largely reactive, often detecting diseases at advanced stages when treatment effectiveness is reduced. This challenge underscores the need for predictive, cost-effective, and data-driven healthcare solutions. This study presents a conceptual framework that integrates metabolomics with artificial …
Published in Emerging Trends in Metabolites · Vol. 3, Issue 2, 2026 Read article
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COMPARATIVE SEISMIC RESPONSE OF IRREGULAR HIGH-RISE RCC 25 STOREY BUILDINGS WITH AND WITHOUT SHEAR WALLS CONSIDERING P–DELTA EFFECT
Abstract: The seismic performance of high-rise reinforced concrete (RCC) buildings is significantly affected by plan irregularity, lateral stiffness distribution, and second-order (P–Delta) effects. Irregular structural configurations may generate torsional response and increased deformation demand under seismic excitation while geometric nonlinearity further amplifies displacement and internal forces in tall structures . This study presents a comparative seismic assessment of a G+24 storey RCC building having overall plan dimensions of 30,000 mm × …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 2, 2026 Read article
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Smart Agriculture in India: Advancements in Image Processing for Automated Plant Disease Detection and Crop Analysis
Abstract: The adoption of image processing technologies in agriculture is emerging as a revolutionary method for tackling persistent challenges in the farming industry. These techniques are increasingly used for different tasks such as detecting plant diseases, assessing crop health, and predicting yields, especially in the framework of smart agriculture systems. This study paints a detailed picture of the latest progress in image processing techniques applied to automated disease detection and detailed …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 13–19 Read article
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Real-Time Deepfake Detection in Video Conferencing Systems
Abstract: Deepfake technology presents non-exemplary threats to video conferencing platforms, enabling advanced fraud, impression and misinformation campaigns worth billions annually. Current detection methods either exhibit latencies exceeding 100ms or rely on server-side cloud processing, raising privacy concerns. This paper presents DeepConfGuard, a lightweight hybrid architecture combining MobileNetV2 for spatial feature extraction, a bidirectional LSTM with attention for temporal modelling, and EfficientNetV2 for refinement. It reaches 94.8% accuracy with 85 ms end‑to‑end …
Published in International Journal of Electronics Automation · Vol. 4, Issue 2, 2026 Read article
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Signal Feature Extraction and Machine Learning Techniques for Human Activity Recognition
Abstract: Human Activity Recognition (HAR) has emerged as a critical field of study with diverse applications in healthcare, fitness tracking, smart homes, and human-computer interaction. The aim of this research is to create an efficient HAR system through advanced techniques characterized by signal feature extraction and machine learning algorithms. The MEMS sensors are used appropriately during data mining to extract time-domain, frequency-domain, and statistical features, which are subsequently passed to the …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 1, 2025 · pp. 24–41 Read article
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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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A Study on “Clean" in Beauty: A Machine LearningApproach to Ingredient Transparency and ConsumerTrust
Abstract: The burgeoning "clean beauty" market, while driven by consumer demand for safer and more sustainable products, is plagued by ambiguous definitions and the pervasive challenge of "greenwashing". This ambiguity hinders informed consumer choices and complicates brand authenticity. This study addresses these complexities by developing a novel machine learning (ML) framework designed to objectively analyze cosmetic ingredient lists, classify products based on their "cleanliness" profile, and identify key ingredient attributes that …
Published in Recent Trends in Cosmetics · Vol. 3, Issue 1, 2026 · pp. 1–12 Read article
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Express-U: Real-time Indian Sign Language Recognition
Abstract: This study describes a system that recognizes Indian Sign Language (ISL) hand poses and gestures in real time using the Hand Tracking Algorithm and the LSTM Deep Learning model. This approach aims to close the communication gap between those who are deaf or hard of hearing and the rest of society. Existing solutions either have a low level of accuracy or do not operate in real time. On both measures, …
Published in Journal of Open Source Developments · Vol. 9, Issue 1, 2022 · pp. 17–22 Read article
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VolleyNexis AI: A Multimodal Artificial Intelligence Framework for Opponent Strategy Prediction, Tactical Intelligence, and Athlete Performance Optimization in Volleyball
Abstract: The rapid advancement of Artificial Intelligence (AI) has profoundly transformed sports analytics, enabling deeper insights, real-time data analysis, and enhanced performance predictions. Noticeable results have been seen by enabling automated analysis of complex gameplay patterns along with athlete performance. Volleyball is a dynamic and strategic sport, which requires continuous tactical adjustments and constant monitoring of the player’s performance. This paper presents VolleyNexis AI, which is a multimodal artificial intelligence framework …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 2, 2025 Read article
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Data-Driven Life Prediction of Fiber-Reinforced Polymer Composites Using IoT Sensing and Machine Learning Algorithms
Abstract: The accurate prediction of fatigue life in fiber-reinforced polymer (FRP) composites remains a major challenge due to their nonlinear, multi-mechanism degradation behavior under variable loading conditions. This study presents a data-driven framework, H-LiProNet, which combines real-time IoT sensing with hybrid machine learning to estimate remaining useful life (RUL) in FRP composites. The proposed system integrates embedded Fiber Bragg Grating (FBG) and acoustic emission (AE) sensors to capture strain and damage …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 116–130 Read article
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VeriSci—AI-Based Multi-Modal Research Assistant
Abstract: The exponential growth of scientific literature is a major bottleneck for academic researchers who want to efficiently discover, assess, and synthesize relevant scholarly knowledge. Traditional methods of literature review are heavily reliant on manual keyword searching, human screening, and subjective data extraction, making them time-consuming, susceptible to cognitive bias, and less effective as the tidal wave of information continues to grow. To overcome these limitations, this study introduces VeriSci, an …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 2, 2026 · pp. 20–27 Read article
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Synthesis of Silver Nanoparticles of Cissus Quandrangularis and It’s Virtual Screening Against Gastric Cancer
Abstract: Gastric cancer, also known as stomach cancer, is the third leading cause of cancer-related deaths globally and remains a major health challenge due to its poor prognosis and high mortality, largely attributed to late-stage diagnosis. In this context, plant-based nanomaterials are gaining momentum for targeted therapeutic applications. Cissus quadrangularis, a medicinal plant native to India from the Vitaceae family, is traditionally used for its diverse healing properties. Its stem, in …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1551–1569 Read article
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Improved Melanoma Recognition using Score Fusion Framework based on Deep Classifiers
Abstract: Melanoma is a fast-growing and malignant cancer that affects neural crest-derived cells of the skin. Early detection is the key to survival and rapid recovery; however, typical diagnosis is based on visual inspection by expert dermatologists. Many melanoma recognition methods have been proposed in the literature that can classify lesions, based on hand-crafted as well as deep learning-based features. However, an accurate, automated method for melanoma is still required. This …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 8, Issue 2, 2021 · pp. 25–33 Read article
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Automated Evaluation of Descriptive Answers
Abstract: This paper offers a smarter system of automatic evaluation of descriptive responses in educational tests. The time-consuming aspect of testing with traditional manual marking, the subjectivity of that process, and the impossibility of scaling it makes it inapplicable, particularly to large academic environments. To resolve the issues, the proposed solution combines the methods of Natural Language Processing (NLP) and hybrid image-text processing on the responses of handwriting and typed answers. …
Published in Emerging Trends in Languages · Vol. 3, Issue 2, 2026 · pp. 1–9 Read article