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103 articles for “Digital classification”
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A Deep Survey on Techniques Used to Recognize Locust Based on CNN
Abstract: The major threat in agriculture is insect pests and crop disease. Outbreaks and upsurges of insects can cause huge loss to crop production. Locusts are crop devouring pests found in many parts of the world. Recognition of locusts in early stage helps to prevent the spread of locusts by taking appropriate counter-measures and biological control methods. Initially, locusts were classified and recognized manually which is time consuming and requires taxonomic …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 1, 2021 · pp. 1–8 Read article
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People Perspective about Evolving, Brains of Givers or Takers!
Abstract: The psychobiologist’s classification of left brained and right brained people advices how the stimulus may be designed for ensuring the growth of each type, or, as to how each may be taught or what vocation be prescribed for them. Viz. the right brained people were seen to venture more into artistic pursuits and being less analytical might face learning problems. On the other hand the left or digital brained people …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 6, Issue 3, 2016 · pp. 24–32 Read article
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Advances in Deep Learning for Medical Image Analysis in the Era of Precision Medicine
Abstract: Medical imaging is fundamental to modern healthcare but analyzing the high-dimensional data requires advanced techniques. Manual image interpretation is time-consuming, subjective and limited in detecting complex patterns and minute details. Recent breakthroughs in Deep Learning offer transformative advances for unlocking clinically relevant information from medical images. This paper provides a comprehensive 6000+ word review of the current state-of-the-art Deep Learning techniques for medical image analysis including detailed coverage of key …
Published in Research and Reviews : Journal of Computational Biology · Vol. 12, Issue 2, 2023 · pp. 10–23 Read article
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The Significance of Documentation in Library Science: Preserving Knowledge for Future Generations
Abstract: In an era characterized by the relentless march of digital progress, the role of documentation in library science remains a steadfast and essential foundation for the preservation and dissemination of knowledge. This paper delves into the enduring significance of documentation within the field of library science, emphasizing its critical role in safeguarding information for the benefit of future generations. The paper begins by highlighting the historical evolution of documentation practices …
Published in Journal of Advancements in Library Sciences · Vol. 10, Issue 2, 2023 · pp. 45–48 Read article
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DEM Processing Methods
Abstract: Digital elevation model (DEM) is used generically to mean the digital cartographic representation of the earth in any form, rectangular grids or lattices, triangular networks or irregular spot heights, and breaklines. This paper aims to present a review of recent techniques used in satellite image processing, especially with focus on DEM processing. The reviewed approaches are classified according to the various techniques used in processing DEM, various filters used in …
Published in Journal of Remote Sensing & GIS · Vol. 4, Issue 1, 2013 · pp. 13–28 Read article
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The Evolution and Impact of Numbers: From Ancient Tallies to Quantum Computing: Review Article on Numbers
Abstract: Numbers are among the most fundamental constructs in human civilization, serving as the backbone of mathematics, science, technology, and virtually every aspect of daily life. They represent not only quantities and measures but also relationships, structures, and patterns that underpin the fabric of human understanding. From the earliest tallies etched on bones by prehistoric humans to the sophisticated numerical systems embedded in today’s artificial intelligence and quantum computing, the evolution …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 3, 2025 · pp. 15–19 Read article
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Application of Geo-Informatics for Cadastral Level Land Use/Land Cover Mapping in Adalpur Micro Watershed of Mahendergarh District for Sustainable Agriculture Management
Abstract: This work represents the case study of Adalpur Micro watershed cadastral level land use/land cover (LULC) mapping for sustainable agricultural management. . This area is situated in Krishnawati seasonal river drainage area. IRS P-6 LISS-IV satellite images for two crop seasons (Rabi and Kharif) of the year 2007 were used to delineate LU/LC within the watershed area. The Rabi and kharif season data are interpreted digitally for delineation of land …
Published in Journal of Remote Sensing & GIS · Vol. 5, Issue 3, 2014 · pp. 36–41 Read article
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Bangla Handwritten Digit and Basic Letter Recognition Using Machine Learning Techniques
Abstract: AbstractThe usage of computer is increasing day by day in Bangladesh, so the use of Bangla is increasing in computer. Furthermore, the use of Bangla handwritten character is also increasing in many computer applications. There exist many techniques for recognition of handwritten character. From the studies we see that machine learning techniques are better techniques for recognition of handwritten character than others. A necessary prerequisite for measuring the performance of …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 3, 2016 · pp. 1–15 Read article
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Fake Cryptocurrency Detection Using Python
Abstract: This study investigates the use of Python-based techniques for detecting fraudulent cryptocurrencies, addressing a growing concern in the digital financial ecosystem. The research methodology integrates various data science approaches, including web scraping, API integration, and advanced data analysis using Pandas and NLTK. Machine learning models, particularly classification algorithms such as Random Forest, are employed to analyze key features extracted from cryptocurrency whitepapers, social media discussions, and transactional data. By training …
Published in Recent Trends in Programming languages · Vol. 12, Issue 1, 2025 · pp. 1–7 Read article
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Intelligent Document Scanner
Abstract: AbstractThere is an irresistible trend in the present world for scanning the paper documents and convert it into a digitalized format. Most of these scanning treat the whole document as an entire image. In this scenario, we propose a novel “Intelligent Document Scanner” which automatically segment and classify the contents of the image document including texts, tables and images and store it as a PDF document with three sections that …
Published in Journal of Computer Technology & Applications · Vol. 7, Issue 2, 2016 · pp. 47–57 Read article
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Study and Analysis of Digital Counters for VLSI Applications
Abstract: AbstractThe counter is a fundamental and essential component. It is used in most digital devices. A counter is a sequential circuit that is used as a counter. The counter is the most widespread application of flip-flops. It is a group of flip-flops in which a clock signal is placed. A counter stores the number of processes related to a clock. It is classified into two categories. The number of flip-flops …
Published in Recent Trends in Programming languages · Vol. 7, Issue 3, 2020 · pp. 17–24 Read article
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Enhancing Customer Engagement with AI-Driven Movie Recommenders: Integrating Neural Collaborative Filtering, Sentiment Analysis, and Conversational Agents
Abstract: In today’s competitive digital landscape, user engagement is a critical factor for the success of entertainment platforms, especially those offering movie recommendations. This study introduces a comprehensive AI-driven framework designed to enhance customer interaction, satisfaction, and loyalty through the intelligent integration of multiple deep learning models. The system combines three core components: Neural Collaborative Filtering (NCF) for generating personalized movie recommendations based on user behavior and preferences, Long Short-Term Memory …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 45–54 Read article
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Advancement in Image Classification: Media Player Control Using Hand Gestures
Abstract: We explore the development of picture categorization methods in this paper, with an emphasis on how they are used to manipulate media players with hand gestures. Our investigation focuses on the development of machine learning techniques, particularly on supporting vector machines (SVM) and convolutional neural networks (CNN). SVMs are used to identify and authenticate people from digital photos or video clips, but CNNs are great at face detection, which is …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 1–10 Read article
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A New Systematic Approach of Using SVM, KNN, PNN and CNN to Achieve Higher Accuracy for Classification and Recognition of Music Genre
Abstract: In order to overcome challenges like finding songs that are similar, figuring out which cultures would enjoy particular music, conducting surveys, and using music as therapy, classification and recognition of music genres are essential. The expansion of music-related content available online has created new opportunities for the development of music referral systems, which support user communities in searching, finding, sharing, and producing digitally. Our aim is to develop a systematic …
Published in Journal of Operating Systems Development & Trends · Vol. 10, Issue 1, 2023 · pp. 1–11 Read article
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Enhancing Online Security: Machine Learning Methods for Phishing Detection—Literature Survey
Abstract: Phishing attacks represent a substantial online security threat as they mimic authentic websites to trick users into disclosing sensitive information. Detecting these malicious websites is crucial for safeguarding user data and maintaining digital trust. This summary provides insight into the application of machine learning methods in the identification of phishing websites. Machine learning, which falls under the umbrella of artificial intelligence, has proven to be a robust instrument for automating …
Published in Journal of Web Engineering & Technology · Vol. 10, Issue 3, 2023 · pp. 29–34 Read article
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DESIGN OF SCRAP COLLECTION AND REWARD MACHINE USING VERILOG HDL
Abstract: The growing amount of waste produced in urban environments has led to a demand for effective and automated recycling solutions. In this paper, a scrap collection and reward machine is designed and implemented using the Verilog Hardware Description Language (HDL). The proposed system is developed to provide a reliable and automated approach for managing recyclable materials while motivating users through a reward-based mechanism. The design includes scrap input interfaces, a …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 1, 2026 · pp. 37–45 Read article
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Cloud-driven Fraud Detection: Evaluating Decision Tree and Random Forest Classifiers for Credit Card Transaction Security
Abstract: With the alarming rise in global financial fraud, necessitating substantial annual losses, modern techniques for fraud detection are continuously evolving across various business domains. Fraud detection involves constant monitoring of user activities to estimate, perceive, or prevent undesirable behaviour. Cloud Computing emerges as a promising solution, accelerating application deployment, fostering creativity and innovation, reducing costs, and enhancing overall business acumen. This study introduces a cloud-driven approach to fraud detection, specifically …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 1, 2024 · pp. 13–27 Read article
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Integrated, Geospatial Risk Assessment of Air, Water, and Soil Pollution Impacts on Agricultural Sustainability using Advanced Digital Technologies
Abstract: The systemic threat posed by the convergence of air, water, and soil contaminants represents a critical challenge to global agricultural resilience and food security. Traditional, site-specific pollutant monitoring methods are insufficient for capturing the dynamic, diffuse, and often nonlinear nature of environmental risk pathways that permeate agrarian landscapes. This study presents a robust framework for comprehensive risk assessment utilizing a synergistic suite of modern tools designed for spatial, temporal, and …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 2, 2025 · pp. 28–37 Read article
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Font-Based Text Steganography for Covert Communication in Devanagari Script: A Review (2020–2026)
Abstract: Steganography hides the fact that a communication exists rather than merely safeguarding its content. Text is the most challenging of all steganographic media because it contains the least redundancy and is the most sensitive to changes. Devanagari script, with its conjunct consonants, ligatures, matras, and non-linear glyph construction, makes these difficulties even harder, rendering rendering-dependent and OCR- based steganographic methods largely ineffective. This paper presents a systematic review of text …
Published in Emerging Trends in Languages · Vol. 3, Issue 2, 2026 · pp. 22–33 Read article
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Sign Language-enabled Offline IP-based Video Call Intercom System for the Deaf
Abstract: Individuals who are deaf or hard of hearing frequently encounter major communication challenges on digital platforms because sign language support is often insufficient. This study presents a real-time, internet-independent sign language-to-text translation system embedded in an offline IP-based video intercom, designed to facilitate seamless communication. Leveraging TensorFlow’s Convolutional Neural Network (CNN) for classification and MediaPipe for hand tracking, the system achieved a training accuracy of 94.24% and a validation accuracy …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 53–66 Read article