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103 articles for “Digital classification”
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A Supervised Learning Approach for Toxic Comment Detection on Social Media Platforms
Abstract: Nowadays everyone uses social media platforms like X (formerly Twitter), Instagram, Facebook, etc. for various purposes. With the help of this, we share our opinions, ideas, and feelings. Generally, the datasets obtained from the internet are constructive; however, there is a significant proportion of toxic ones. The datasets are filtered to remove noise, and noise is removed in post-processing. The study initiates with the upload and preprocessing of a toxic …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 11, Issue 2, 2024 · pp. 7–14 Read article
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Diagnosis of Breast Cancer by Image Processing and Acquisition
Abstract: Abstract— Cancer is one of the deadliest disease in the current world and among breast cancer is found about 24%-28% among all the reported cases. In this paper development of CAD systems is discussed which reduces human interference and increases preciseness in the diagnosis of breast cancer. Mammography is a technique widely followed by radiologists for the detection and diagnosis of tumors. Introduction of digital imaging helped in acquiring high …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 6, Issue 2, 2019 · pp. 30–36 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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Under Voltage and Over Voltage Protection of Electrical Equipment - A Review
Abstract: In our modern, digitally-driven world, the seamless operation of electrical equipment is paramount, spanning industries, households, and infrastructure. However, the reliability of these vital assets is inextricably linked to the quality of electrical power supplied to them. Voltage fluctuations, specifically under voltage and over voltage events, pose significant threats to the integrity and functionality of electrical equipment. This review paper undertakes a comprehensive exploration of under voltage and over voltage …
Published in International Journal of Electrical Power and Machine Systems · Vol. 2, Issue 2, 2024 · pp. 1–9 Read article
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An Analysis of Multimodal Fusion in Deepfake Detection for Video Samples
Abstract: In today’s rapidly evolving digital landscape, deepfake technology stands as both a marvel and a threat to privacy and security. Deepfakes, hyper-realistic synthetic media created using artificial intelligence (AI), can deceive and manipulate on an unprecedented scale, from political propaganda to compromising videos of public figures. This research navigates deepfake detection, focusing on two advanced methodologies: the vision transformers (ViT) image classifier and the Meso4 method. The ViT model utilizes …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 19–27 Read article
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Defect Detection in Patterned Fabrics Using Local Binary Pattern and Its VLSI Implementation
Abstract: For texture classification in computer vision Local Binary Patterns (LBP) is used as one of the efficient method. In this paper, LBP texture operator is used to label the pixels of an image of any fabric or texture using the property of thresholding the neighborhood of each and every pixel and considers the compared result as a binary number or a digit which will be used for detecting the defects …
Published in Journal of Microcontroller Engineering and Applications · Vol. 1, Issue 1, 2015 · pp. 45–51 Read article
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Revolutionizing Agriculture: Botani Scan’s Deep Learning for Plant Disease Diagnosis
Abstract: Crop disease detection is of key importance because of its role in food safety but infrastructural issues still hamper diagnosis in most regions worldwide. Accurate plant disease identification is essential to secure food, predicting yield decline and managing epidemic outbursts. The advent of digital cameras along with the progress of computer vision technology brings to light the mounting demands for the development of automated disease detection methods in precision agriculture, …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 1, 2024 Read article
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A Review of Machine and Deep Learning Techniques for Cyber Security
Abstract: Nowadays in the digital landscape, cyber threats and attacks are increasing in an exponential manner, posing server risks to organizations and critical infrastructures. Data breaches often result from sophisticated threat models that exploit vulnerabilities in networks, systems and user behaviors. Cyber solutions are increasingly incorporating machine learning and deep learning to prevent and mitigate these security issues. These technologies have the potential to detect anomalies, classify threats and predict potential …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 01–07 Read article
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A Comprehensive Review: Personalized Treatment Strategies in Stable Ischemic Heart Disease
Abstract: Stable Ischemic Heart Disease (SIHD) is one of the leading cardiovascular disorders associated with high morbidity and mortality worldwide. Since early symptoms such as chest pain, fatigue, and shortness of breath are often non-specific and difficult to recognize, diagnosis becomes challenging, and many cases remain undetected until advanced stages or complications occur. Traditional diagnosis depends heavily on clinical evaluation, electrocardiography, stress testing, and imaging techniques. The development of improved treatment …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 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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AI-Based Cybersecurity Framework for Protecting Smart Surveillance Infrastructure in Mumbai
Abstract: Smart city infrastructures increasingly rely on interconnected surveillance systems to ensure safety, operational efficiency, and public trust. However, the rapid expansion of IoT-based monitoring technologies has introduced new cyber risks, especially in high-density metropolitan areas. This paper proposes an AI-driven cyber resilience framework targeting smart surveillance infrastructure as a critical smart-living domain, focusing on Mumbai as a case study. Using the CIC-IDS2017 dataset, a machine learning-based intrusion detection model is …
Published in Journal Of Network security · Vol. 14, Issue 1, 2026 Read article
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Smile Detection Techniques in Real-time Video Environment
Abstract: Humans have very good visual system which helps to identify people and objects, perform operations, drive vehicle, read text and so on. Although it might be seen that humans do not take special effort to do most of these tasks. Human visual system is fairly complex to replicate and implement. Computer vision in the simplest term is an automation of human visual system, so that computer and machines obtain high …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 8, Issue 2, 2021 · pp. 40–46 Read article
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Classification Of Music Genre Using Machine Learning
Abstract: Machine Learning is a way that helps the systems to automatically learn from experience and improve the performance and predict the outcome more accurately without any requirement of being explicitly programmed. Music is one of the most significant and influential part of people’s life. Also, music is known as a universal language as it has the power to unite people from different places and cultures. This helps in the recognition …
Published in Journal of Instrumentation Technology & Innovations · Vol. 12, Issue 1, 2022 · pp. 11–16 Read article
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Landuse and Landcover analysis using Remote Sensing and GIS: A case study in parts of Kadapa District, Andhra Pradesh, India.
Abstract: Digital change detection techniques by using multi-temporal satellite imagery helps in understanding landscape dynamics. The present study illustrates the spatio-temporal dynamics ofLand use/cover of around Chennur, Kadapa District, Andhra Pradesh India. Landsat satellite imageries of two different time periods, i.e., Landsat Thematic Mapper (TM) were acquired by earth explorer site and quantify the changes in the study area 2005-2006 to 20015-16 over a period of 10 years. Supervised classification methodology …
Published in Journal of Remote Sensing & GIS · Vol. 9, Issue 3, 2018 · pp. 1–7 Read article
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Machine Learning Based Smart Aquaponics Farming System
Abstract: For many years, researchers have been studying nutrient management in aquaponic systems. Most have concentrated on adequate nutrition control in an aquaponic setup, but there has been relatively little study on commercial scale applications. For plant growth, it is necessary to measure the level of nutrients present in the soil mixture. In our model, the input data was sourced on some interval of time basis from three commercial aquaponic farms. …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 10, Issue 1, 2022 · pp. 30–37 Read article
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Object Detection Using Deep Learning Algorithm
Abstract: Object detection is a computer technology related to computer vision and image processing that deals with detecting images of semantic objects of a certain class (for example cars, buildings, etc.) in digital images and videos. To detect objects, there are many algorithms available, in this paper YOLO algorithm is explored for detection of objects on real-time data. You Only Look Once (YOLO) is a state-of-the-art real time object detection system …
Published in Journal of Control & Instrumentation · Vol. 12, Issue 2, 2021 · pp. 1–13 Read article
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Enhancement of Digital Mammograms Using Intuitionistic Fuzzy Entropy Function
Abstract: A novel intuitionistic fuzzy entropy-based algorithm is developed for increasing the contrast of digital mammograms. The contrast enhancement helps in the early detection of masses and microcalcification in tissues thus paving the way for the auxiliary diagnosis of breast cancer. The current techniques for the enhancement of digital mammograms do not consider the uncertainty in pixel intensities of mammograms. The proposed technique aims at enhancing the mammograms using intuitionistic fuzzy …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 10, Issue 2, 2023 · pp. 10–26 Read article
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Credit Card Fraud Detection Using Machine Learning Techniques
Abstract: Credit card fraud has become a significant concern in today's digital economy, with billions of dollars being lost annually to fraudulent transactions. Conventional rule-based approaches frequently prove inadequate in addressing the constantly changing strategies employed by fraudsters. Machine learning methods have emerged as robust solutions for detecting credit card fraud, presenting the capability to accurately identify fraudulent transactions promptly. In this study, we investigate the efficiency of three widely used …
Published in Journal of Open Source Developments · Vol. 11, Issue 1, 2024 · pp. 1–7 Read article
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Gradient Boosted Regression Tree Approach to Predicting Toxic Interactions on X and YouTube
Abstract: In the digital age, social media platforms play a vital role in facilitating user engagement, encompassing both positive interactions and avenues for negative, often harmful behaviors. Recognizing and addressing toxic exchanges is paramount to nurturing healthy online communities and preserving users’ well-being. This study introduces a novel method for identifying toxic interactions by utilizing Gradient Boosting Regression Trees (GBRT) algorithm, a machine learning approach renowned for its exceptional accuracy and …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 3, 2025 · pp. 7–14 Read article
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AI-Based Sentiment Analysis of Public Perception Under Bangabandhu Sheikh Mujibur Rahman
Abstract: Sheikh Mujibur Rahman, known as Bangabandhu, played a pivotal role in Bangladesh’s post-liberation period (1971–1975). Understanding public sentiment during his leadership is crucial for historical analysis. This study employs Artificial Intelligence (AI)-based Sentiment Analysis to examine public perception through archived newspapers, parliamentary speeches, and historical records. Using Natural Language Processing (NLP) techniques, including sentiment classification and opinion mining, we analyze textual data to assess the prevailing public mood during his …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 21–29 Read article