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103 articles for “Digital classification”
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Anthropogenic Land Use Change Detection in a Kashmir Himalayan Watershed – A Remote Sensing and GIS Approach
Abstract: Watersheds are ubiquitous units that can be seen as the physical foundation of the nation. They have long been recognized as desirable units for planning and implementing developmental programs. Human impact on the watersheds is increasing day by day. The alteration of land use pattern in the Himalayan watersheds is increasing the vulnerability of these inherently fragile ecosystems. The present study is conducted in a Himalayan watershed of Lidder catchment …
Published in Journal of Remote Sensing & GIS · Vol. 5, Issue 1, 2014 · pp. 34–42 Read article
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CiviCare: An AI-Powered Smart Water Governance and Grievance Resolution System for Urban Local Bodies in India
Abstract: Water supply operations in many Indian Urban Local Bodies (ULBs) continue to rely on manual processes that lack transparency, efficiency, and accountability. Citizens often have limited access to information regarding supply schedules, connection status, and billing details. Grievances are frequently reported through informal channels, resulting in poor traceability and lack of resolution assurance. This paper introduces CiviCare, a full-stack AI-enabled web platform designed to digitize and optimize municipal water governance …
Published in Journal of Web Engineering & Technology · Vol. 13, Issue 2, 2026 · pp. 15–23 Read article
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A Profound Analysis on Complex Multiclass BCI Signals Classification by an EEG Device
Abstract: With a major shift in the technology paradigm today in the area of deep learning and artificial intelligence, one of its important applications today is found in brain-computer interface (BCI). Brain computer-interface, also known as neural control interface or mind-machine interface is a device that helps a user to interact with a computer using only his brain-activity, which is measured usually by Electroencephalography (EEG). The usage of such mechanism has …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 8, Issue 1, 2021 · pp. 22–44 Read article
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Music Recommendation System Using Big Data and Machine Learning
Abstract: In comparison to earlier times, there is now a wealth of music available thanks to the development of music streaming services that can be used from mobile devices. Classifying digital music can be timeconsuming and cause fatigue. Obtaining one’s favorite music from the huge music selection has become a problem. The creation of a music recommendation system that can search through music libraries and make song recommendations to users based …
Published in Journal of Open Source Developments · Vol. 9, Issue 3, 2022 · pp. 18–24 Read article
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Accelerating Unsupervised Feature Learning: Parallelized Training of Denoising Autoencoders
Abstract: Unsupervised representation learning has become a cornerstone of contemporary machine learning, enabling algorithms to extract informative features from un-labelled, high-dimensional data. This work investigates the efficacy of stacked denoising autoencoders (SDAEs) trained via parallelized stochastic gradient descent (SGD) as a scalable approach to feature extraction. By strategically leveraging multi-threaded computation, our study systematically examines the trade-offs between increased parallelism, training efficiency, and the preservation of model accuracy. Experiments on the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 56–64 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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Design and Development of Agrobot Using Feed Forward Network for Smart Farming Agriculture
Abstract: The Agrobot framework is a form of natural language processing that requires training to understand human language and meet user needs accordingly. The development of a chatbot tailored for the agricultural industry represents a significant advancement in agricultural technology. This chatbot serves as an interactive tool to assist farmers in various aspects of agricultural practices, including crop management, pest control, weather forecasting, and market information. The main objective of this …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 1, 2024 · pp. 6–14 Read article
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Handwritten Digit Recognition Using Logistic Regression, SVM, KNN and CNN Algorithms
Abstract: The style of handwriting varies from person to person. Handwritten numbers are not always the same size, orientation and width. To develop a system to understand this, the machine recognizes handwritten digit images and classifies them into 10 digits (from 0 to 9). The recognition of handwritten digits is a technology which is used for the automatic recognizing and detecting handwritten digital data through various deep lerning and machine learningmodels. …
Published in Journal of Operating Systems Development & Trends · Vol. 9, Issue 2, 2022 · pp. 20–28 Read article
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Identification of Handwritten Digits using Machine Learning
Abstract: Handwritten Digit Recognition is one of the practical issues in sample recognition applications. The task for handwritten recognition has been difficult due to various variations in written styles. The capacity to create an effective algorithm that can detect handwritten numbers given by users via a scanner, tablet, and other digital devices is at the core of the issue. Artificial intelligence is used in machine learning, which automatically corrects errors based …
Published in Journal of Operating Systems Development & Trends · Vol. 10, Issue 1, 2023 · pp. 19–26 Read article
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Nail Image Processing for Early Symptom Detection of Diseases based on Supervised Learning
Abstract: Digital Image Processing of human nail can be used for the prediction of various systemic and dermatological diseases. The proposed system – Nail Image Processing System using SVM (NIPS-S) helps us to create a model for the analysis of human nail and predict various diseases. The input to the proposed system is the Human Palm Image. The nail portion is segmented and a combination of nail color, shape and texture …
Published in Journal of Computer Technology & Applications · Vol. 8, Issue 3, 2017 · pp. 49–61 Read article
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Automatic Fake News Detection: A Review
Abstract: Misinformation has exploded in the last two decades with the development of digital technologies. The damage caused by it to social harmony, peace, social trust, justice, and democracy has increased the necessity of automatic identification of bogus news and intervention. As more and more content is being available, a person may not deliver much attention to a news piece and may assume it to be reliable just from reading headlines. …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 10, Issue 1, 2023 · pp. 29–35 Read article
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Machine Learning Innovations for Effective Spam Comment Filtering in Social Networks
Abstract: The increasing prevalence of social media platforms has revolutionized communication, fostering unparalleled levels of connectivity and data exchange. However, the widespread increase in spam comments presents a serious threat to the integrity of online discussions, potentially undermining the quality of interactions. To confront this issue, our proposed model utilizes machine learning techniques to bolster spam comment detection across various social media platforms. This endeavor involves a thorough investigation encompassing data …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 2, 2024 · pp. 19–24 Read article
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Optical Character Recognition Using Back Propagation Neural Network
Abstract: This paper represents an Artificial Neural Network (ANN)-based approach for the recognition of English characters using feed-forward neural network. Noise has been considered as one of the major issues that degrades the performance of character recognition system. Our feed forward network has one input, one hidden, and one output layer. The entire recognition system is divided into two sections, namely training and recognition section. Both the sections include image acquisition, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 2, 2016 · pp. 11–18 Read article
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Identification of Diabetic Foot Ulcer by Using Filter and Pixel Classification Methods
Abstract: Ulceration of the foot in diabetes is common and disabling and frequently leads to amputation of the leg. Mortality is high and healed ulcers often recur. The pathogenesis of foot ulceration is complex, clinical presentation variable, and management requires early expert assessment. Interventions should be directed at infection, peripheral ischaemia, and abnormal pressure-loading caused by peripheral neuropathy and limited joint mobility. Despite treatment, ulcers readily become chronic wounds. Diabetic foot …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 2, Issue 1, 2015 · pp. 22–31 Read article
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Digital Transactions System
Abstract: In this paper, a cryptographic application is presented as Digital Transaction System (DTS). DTS requires the high level security protocol. There are various attacks considered successfully on DTS. The claim of the security of DTS holds the short time. Thus, it requires updating frequently. The single hardness of the problem is not enough but the compact problem is recommended to design such DTS. This work is based on the study …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 7, Issue 2, 2020 · pp. 18–24 Read article
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Optimizing Sentiment Analysis with Naïve Bayes and Random Forest Techniques: A Result-based Approach
Abstract: In the increased digitalization, the sentiment analysis and classification have evolved as an eminent area to determine the polarity of positive, negative, and neutral reviews of the customers and users on products. It is an integral application field that employs supervised learning, Machine Learning, and Natural Language Processing concepts. The proposed Semantic Analysis and Classification using Naive Bayes and Random Forest system accomplishes the sentiment polarity by classifying the user …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 46–57 Read article
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Effective CBIR System Using Color Histogram and Distance Measures
Abstract: AbstractInterests to precisely retrieve desired images from databases of medical images are developing every day. Certain features define the images; on the basis of those, the retrieval of images is facilitated. These components incorporate texture, color, shape and region. A lot of work has been done in this direction to discover the new ways to use these features in image retrieval process. In this study, we exhibit an overview of …
Published in Journal of Web Engineering & Technology · Vol. 6, Issue 1, 2019 · pp. 11–14 Read article
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Prediction of Mobile Phone Price Using Machine Learning Classifiers
Abstract: One cannot imagine one's life without mobile phones; in today's digital era, mobile phones have become a necessity for everyone to fulfil their various demands like messaging, communication, entertainment, productivity, research, shopping and many more. In a thriving market of mobile phones where new smartphones are launched every year with new advanced features and various designs, determining the expense of a mobile can be a trouble-some tasks for consumers. In …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 101–108 Read article
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Secure Forge: Deepfake Image Detection Using Vision Transformers
Abstract: Deepfake technologies have become a major risk to the credibility and trustworthiness of digital visual information. Using powerful generative models like GANs and autoencoders, deepfakes can generate highly realistic fake videos and images, resulting in misinformation, identity theft, and public loss of trust in digital media. Classic Convolutional Neural Networks (CNNs) while being highly effective in initial-stage, deepfake detection tend to be limited by their local receptive fields and dependency …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 32–45 Read article
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A Novel Multi-Wavelet Based Image Filtering Technique for Noise Reduction in Mammographic Medical Images
Abstract: The digital mammographic imagery is often influenced by various types of noises and thus requires application of various filters to denoise the noise level in order to preserve the vital imagery contents. This evidently helps the medical practitioner to improve the image quality of the mammograms and helps them in giving accurate diagnosis. Though there are several works on image denoising algorithm but they aren’t much to pay emphasis over …
Published in Journal of Advanced Database Management & Systems · Vol. 2, Issue 1, 2015 · pp. 12–17 Read article