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1972 articles for “feature” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Automated Plant Disease Detection and Treatment Advisor Using Artificial Intelligence
Abstract: Automated plant disease detection and treatment advisors using artificial intelligence represent a significant advancement in modern agriculture. The identification of plant leaf diseases is essential to maintaining food security and agricultural output. Machine learning models, particularly deep learning algorithms like convolutional neural networks (CNNs), are trained on labeled datasets containing images of healthy and diseased plants. These models learn to classify images into different disease categories with high accuracy. Convolutional …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 1–7 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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Countering Counterfeiting: Global Challenges and Technological Advances
Abstract: Fake notes are a global issue. Indian is only one among several. Anyone may now print counterfeit notes thanks to advancements in technology. These notes are created without the state’s legal sanction, and the ongoing production of such notes could hurt a country’s economy. When counterfeit notes are created and distributed, ordinary people cannot identify the difference between real and phony money since they are identifiable by their physical qualities. …
Published in Current Trends in Signal Processing · Vol. 14, Issue 2, 2024 · pp. 31–36 Read article
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Fertilizer Prediction Using Machine Learning
Abstract: Fertilizer prediction is a critical aspect of modern agriculture, aimed at optimizing resource utilization while maximizing crop yields. In recent years, machine learning (ML) techniques have emerged as powerful tools for addressing this challenge by leveraging data-driven approaches to predict the optimal type and quantity of fertilizer required for different crops and soil conditions. This research paper provides a comprehensive review of the existing literature and methodologies employed in fertilizer …
Published in Journal of Mechatronics and Automation · Vol. 11, Issue 2, 2024 · pp. 26–35 Read article
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A Comparative Study Between GSM and CNN to Develop Gesture Detection Based Alert System for Women Safety
Abstract: Women’s safety is a pressing issue in today’s world, and technology can play a crucial role in addressing it. This project introduces a facial expression recognition device that uses Convolution Neural Network (CNN) technology and develop it’s comparison with an expression system with use of GSM is done. Unlike traditional methods relying on manual activation or dedicated devices, this system reacts instantly to threatening situations by recognizing predefined gestures, ensuring …
Published in International Journal of Electrical Power and Machine Systems · Vol. 2, Issue 1, 2024 · pp. 24–30 Read article
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Types and Fabrication Methods of Borate Based Thermoluminescence Materials
Abstract: Thermoluminescence (TL) is a kind of luminescence produced by certain crystalline materials that refers to the re-emission of energy received from electromagnetic radiations as light when the substance is heated. Thermoluminescence materials are used in a variety of fields, including environmental dosimetry, personal dosimetry, and medical research. Doping different rare earth impurities in different hosts causes the characteristics of materials suitable for diverse applications in many disciplines to change. Terbium …
Published in Journal of Nuclear Engineering & Technology · Vol. 14, Issue 3, 2024 · pp. 1–11 Read article
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Exploring the Bourne Again Shell (Bash)
Abstract: The Bourne Again Shell (Bash) is a popular command-line interpreter and scripting language, created as a free software alternative to the original Bourne Shell (sh). Developed as part of the GNU Project, Bash extends the functionality of its predecessor by incorporating features from the C Shell (csh) and KornShell (ksh), making it more versatile and powerful. Bash offers robust command-line editing, job control, and support for functions and variables, enabling …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 1, 2025 · pp. 01–09 Read article
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Detection of Phishing Website Using URL
Abstract: Phishing attacks are one of the greatest threats to online security, where fraud websites deceive users into giving out sensitive information. Traditional methods of detection, such as blacklists and heuristic-based systems, often fail in identifying newly created or sophisticated phishing websites. This study proposes an intelligent phishing website detection system using Convolutional Neural Networks (CNNs) in analyzing URLs and associated features. Using labeled URLs, the system employs such attributes such …
Published in Journal Of Network security · Vol. 13, Issue 1, 2025 · pp. 10–15 Read article
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Transfer Learning in Deep Learning Models for Medical Imaging: Utilizing Pretrained Models to Improve Performance in Medical Image Analysis
Abstract: Transfer learning is now a trending technique in deep learning, especially in medical imaging. This technique solves landmark problems by utilizing the pre-trained models, including the limited availability of the annotated medical data and the time-consuming computational costs of training deep learning models from scratch. The generalizability of deep models could increase diagnostic precision for specific medical tasks, require fewer samples to train, and take less time to train due …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 67–85 Read article
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Timestamp Extraction and Log Classification Using Supervised Machine Learning: A Comparative Study
Abstract: In modern software systems, logs are vital for monitoring application behavior, diagnosing issues, and analyzing performance. Timestamps are especially important for sequencing events, identifying anomalies, and understanding system failures. However, detecting timestamps in logs is challenging due to inconsistent formatting across systems and the presence of timestamp-like strings in non-timestamp fields. Traditional rule-based methods often fail in such cases. This study proposes a supervised machine learning approach to accurately classify …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 26–38 Read article
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A Comprehensive Survey on Detection of Video Transitions
Abstract: Video shot boundary detection (SBD) is a fundamental task in the field of video processing and analysis. It plays a critical role in various video applications such as content-based video retrieval, video indexing, editing, summarization, and browsing. Identifying shot boundaries helps segment a continuous video stream into distinct shots, each representing a meaningful visual unit. This segmentation is essential for organizing and interpreting video data efficiently. This study provides an …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 3, 2025 · pp. 17–26 Read article
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A Comprehensive Analysis of Classification Methods for Churn Prediction in Financial Services
Abstract: Persistent issues that affect long-term revenue in the banking sector include excessive client attrition. Customary churn models depend on measures related to customer satisfaction, which often result in low predictive accuracy due to their subjective nature. This study proposes an effective early warning model to address customer churn in financial services. Data is preprocessed through cleaning, one-hot encoding, Z-score normalization, and Min-max scaling. To handle class imbalance, the SMOTE algorithm …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 2, 2025 · pp. 47–61 Read article
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Assessing the Robustness of Machine Learning Models for Wireless Intrusion Detection Under Adversarial Traffic Perturbations
Abstract: As the Internet of Things (IoT) devices and wireless communication networks continue to grow rapidly, protecting systems from cyber threats has become increasingly important. Machine learning–based intrusion detection systems (IDS) have shown strong potential in detecting abnormal and malicious network activities, yet their effectiveness and resilience when facing adversarial attacks are still not sufficiently explored. This research evaluates Machine Learning (ML) models–XGBoost, random forest, and multi-layer perceptron (MLP)—in detecting attacks …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 29–34 Read article
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Data-Driven Energy Forecasting for Smart Homes: Ensemble Learning from IoT Meters and Relevance for Polymer-Composite Based Smart Infrastructure
Abstract: Reliable estimation of household electricity demand is relevant in creating efficiency in energy usage, optimization of the loads, and intelligent demand-side management in intelligent grid systems. This paper introduces a varied machine learning model that approaches residential electric consumption prediction using an assortment of ensemble regression boosts, including Linear Regression, Lasso Regression, Decision Tree Regressor, Random Forest, and Gradient Boosting, to predict residential electricity consumption environments on a time-series arrested …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 29–64 Read article
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Aura Pulse: An AI-Powered System for Real-Time Emotional Support and Personalized Recommendations
Abstract: Aura Pulse is a cutting-edge AI-powered platform developed to provide real-time emotional support, tackling the growing challenges of stress, anxiety, and burnout in today’s fast-moving digital era. Utilizing advanced facial expression analysis, Aura Pulse interprets visual cues to create a comprehensive emotional profile of the user. This instant emotional evaluation enables the platform to deliver personalized suggestions aligned with the user’s mood and mental state, promoting overall well- being and …
Published in Journal of Advancements in Robotics · Vol. 13, Issue 1, 2026 · pp. 18–25 Read article
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A Review on: Cotard’s Syndrome
Abstract: Cotard’s Syndrome is a rare and severe mental health condition characterized by nihilistic delusions, in which individuals firmly believe that they are dead, no longer exist, or that parts of their body are decaying or missing. These beliefs are not symbolic or metaphorical but are experienced as absolute truths, making the disorder particularly distressing and difficult to manage. The syndrome is most commonly observed in association with major depressive disorder, …
Published in Recent Trends in Infectious Diseases · Vol. 3, Issue 1, 2026 · pp. 5–9 Read article
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Design and Development of Multifunctional Stretcher
Abstract: Hospital stretchers and wheelchairs are integrated in this piece. Instead of using the chair and stretcher individually, the suggested stretcher can be utilized for multiple purposes. Patients' mobility issues can be greatly reduced by this arrangement. There is a challenge in the ICU moving seriously damaged or fractured patients from stretcher to wheelchair. This product is capable of addressing such situations. One more advantage of the proposed design to conduct …
Published in International Journal of Industrial and Product Design Engineering · Vol. 4, Issue 1, 2026 · pp. 29–34 Read article
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Multi-Parameter Biomedical Sensor-Based Mental State Classification Using EEG And Deep Learning Techniques
Abstract: With mental health concerns becoming increasingly widespread, there is a strong need for systems that can monitor conditions like stress, anxiety, and fatigue in a continuous and non- invasive manner. This research proposes a novel multi-parameter biomedical sensing framework for mental state classification by integrating electroencephalography (EEG) signals with physiological parameters, including body temperature acquired using LM35 sensors, heart rate from pulse sensors, and blood oxygen saturation (SpO₂) measurements. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 · pp. 1–8 Read article
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Prediction of Mechanical Properties for Advanced Engineering Applications utilizing Polymer Composite Materials by Machine Learning
Abstract: Polymer composites show great promise as engineering materials because of their mechanical performance, resistance to corrosion, lightweight nature, and adaptability in design. Aerospace, automotive, biomedical, maritime, and civil engineers all rely on mechanical property prediction to cut down on trial expenses, expedite product development, and optimize material selection. Speedy design optimization is not possible using traditional numerical and experimental methods due to the high costs associated with material characterisation, computational …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1258–1284 Read article
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Monitoring of Disable Patients with their Medical conditions using K-NN Classifier Algorithm
Abstract: In this paper a general procedure for the infirmity assessment of patients with ineptitudes is presented. It relies upon consistently activity examination using ordinary accelerometer sensors conveyed by the noticed person while at home without clinical staff present. The k-NN classifier is being used to study six different types of activities after preliminary data pre-planning, followed by further decreases in estimation and confirmation time. Promising results are gotten which could …
Published in Current Trends in Signal Processing · Vol. 12, Issue 2, 2022 · pp. 1–7 Read article