Sign inSubmit
Tips: “quotes” for a phrase · author:Lee · a DOI goes straight to its article

413 results for “methods and techniques”

Set a search alert
Research ArticleOpen accessIn the abstractAdvancements In Precision Agriculture: A Review on Image-Based Stress Detection and Predictive Yield Loss ModelingA. Josephine, A. SubhashiniPrecision agriculture utilizes cutting-edge technologies to maximize the management of crops, enhance utilization of resources, and maximize yield forecasting. This study critically analyzes 53 peer-reviewed articles to evaluate advancements in image-based stress detection and yield prediction techniques for precision agriculture. The review enumerates main issues, such as image-based analysis methods, different crop stress aspects (biotic, environmental, and abiotic), and remote … …Journal of Computer Science, Vol. 21, Issue 11 · 28 Dec 2025 · 2,508 accessesView PDFCite
Research ArticleOpen accessIn the abstractLess Biased Approach for Sandstone Pore SegmentationDaffa Abiyyu Murtadha Kurnia, Iman Herwidiana KartowisastroReservoir characterization is a fundamental process in estimating reserves within petroleum and hydrogeological systems, where the precise determination of pore space dictates the validity of fluid flow models. Although X-Ray Computerized Tomography (XRCT) has become the standard non-destructive evaluation method for visualizing the internal structure of rocks, the data interpretation process still faces challenges during the image segmentation stage. Conventional … …Journal of Computer Science, Vol. 22, Issue 6 · 15 Jun 2026 · 1,191 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Brain MR Image Quality Using CNN With Best Denoising Modality for Improved Diagnosis of Abnormality: An AppraisalKavery Verma, Subodh Srivastava, Ritesh Kumar MishraDigital medical images acquired from the brain are highly susceptible to noise, which causes significant challenges for radiologists to identify abnormalities in a precise manner. Noise interference hampers both diagnostic accuracy and the interpretation of underlying abnormalities, potentially leading to flaw conclusions. Magnetic Resonance (MR) imaging is the most preferred digital imaging technique for brain abnormality detection. To achieve precise … …Journal of Computer Science, Vol. 22, Issue 3 · 26 Mar 2026 · 1,462 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Approach for Differentiating AI-Generated and Real Images Using Gabor and Color Layout Filters (GF and CLF)G. Ayyappan, A. Thankaraj, S. Surendran et al.The emergence of generative AI images has profoundly upended the art world. Distinguishing AI-generated images from human-created artwork is increasingly challenging. If this issue remains unresolved, dishonest individuals may exploit those who are willing to pay more for original artwork and businesses whose stated policies exclude AI graphics. There are a number of methods for differentiating AI photos from human … …Journal of Computer Science, Vol. 22, Issue 2 · 3 Mar 2026 · 1,751 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhanced Hybrid Spectrum Sensing Method Using TCDT and IEDT for Cognitive RadioNeha Chaudhary, Rashima Mahajan, Richa Adlakha et al.The development of efficient spectrum sensing techniques has witnessed progressive growth for optimum utilization of spectrum resources in cognitive radio. The primary objective of spectrum sensing is the identification and proper utilization of the spectrum holes. Nowadays, due to the advancement of wireless technologies, the demand for spectrum is also increasing and thus in turn, the requirement for better spectrum … …Journal of Computer Science, Vol. 20, Issue 11 · 20 Nov 2024 · 4,301 accessesView PDFCite
Research ArticleOpen accessIn the abstractLandslide Susceptibility Mapping with GIS in Nagi Dada Area of Panauti Municipality, Kavrepalanchwok District: A Comparison Between AHP and FR MethodArju Bhattarai, HimLal Shrestha, Asim Timalsina et al.Landslide Susceptibility Maps (LSM) are useful for both development planning and disaster management. Currently, LSMs are primarily created using GIS and remote sensing techniques. Landslide susceptibility mapping relies heavily on selecting and weighting causative elements based on their impact on slope instability. GIS is useful for calculating static parameters such as slope and aspect, as well as generating landslide susceptibility … …American Journal of Engineering and Applied Sciences, Vol. 17, Issue 4 · 22 Aug 2024 · 7,093 accessesView PDFCite
Research ArticleOpen accessIn the abstractPM2.5 Prediction Using Homogenous and Heterogenous Ensemble Learning: A Comprehensive EvaluationShrabani Medhi, Minakshi GogoiAir pollution is a global issue. PM2.5 is considered to be the most dangerous pollutant. Prediction of PM2.5 concentration is important so that effective measures can be taken beforehand. A multitude of machine learning methodologies have been employed in forecasting PM2.5 levels, utilizing diverse combinations of ensemble classifiers and regressors. However, there are three important issues that need to be … …Journal of Computer Science, Vol. 20, Issue 9 · 20 Jun 2024 · 5,176 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplication of Unimodular Hill Cipher and RSA Methods to Text Encryption Algorithms Using PythonSamsul Arifin, Dwi Wijonarko, Suwarno, Edwin Kristanto SijabatText encryption is one of the techniques used to maintain the confidentiality of information in digital communications. In this study, we propose to apply a combination of the Unimodular Hill Cipher and RSA methods to a text encryption algorithm using the Python programming language. The Unimodular Hill Cipher method uses an unimodular matrix to replace text characters with encrypted characters, … …Journal of Computer Science, Vol. 20, Issue 5 · 1 Mar 2024 · 6,484 accessesView PDFCite
Review ArticleOpen accessIn the abstractUnleashing the Power of Image Denoising: A Comprehensive Review of Classical to Deep Learning MethodsArchana Saini, Ayush DograImage denoising is a vital step in many image processing and computer vision professions that aims to improve picture quality by decreasing noise while maintaining important image information. In this article, a detailed overview is presented of traditional and deep learning based picture denoising approaches. Classical methods, such as linear filtering, transform domain techniques, and patch-based approaches like Non-Local Means … …Journal of Computer Science, Vol. 21, Issue 8 · 8 Oct 2025 · 3,107 accessesView PDFCite
Review ArticleOpen accessIn the abstractDeep Learning in Early Alzheimer’s Disease’s Detection: A Comprehensive Survey of Classification, Segmentation and Feature Extraction MethodsRubab Hafeez, Sadia Waheed, Syeda Aleena Naqvi et al.Alzheimer’s disease is a deadly neurological condition, impairing important memory and brain functions. Alzheimer’s disease promotes brain shrinkage, ultimately leading to dementia. Dementia diagnosis typically takes 2.8-4.4 years after the first clinical indication. Advancements in computing and information technology have led to many techniques for studying Alzheimer's disease. Early identification and therapy are crucial for preventing Alzheimer's disease, as early-onset … …Journal of Computer Science, Vol. 21, Issue 5 · 26 Apr 2025 · 5,765 accessesView PDFCite