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12 results for “Multi-Temporal Analysis”
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Research ArticleOpen accessIn the keywordsAssessing Supervised Classification Algorithms for Mangrove Detection and Differentiation from Other Forest Types in Paiton District, Probolinggo RegencyKaruniawan Puji Wicaksono, Fathor Rohman, Yasushi MitsudaRemote sensing provides an effective approach for monitoring forest cover dynamics, yet distinguishing mangroves from other forest types remains challenging in heterogeneous coastal landscapes. This study compares six supervised classification algorithms: Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Mixture Discriminant Analysis (MDA), Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) for mangrove detection in Paiton, … …OnLine Journal of Biological Sciences, Vol. 26, Issue 3 · 1 Sep 2026 · 844 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntegrating (OLAP) Online Analytical Processing With a Fast Algorithm for Epileptic Seizures DetectionIlyas Zidane, Wajih Rhalem, Nordine ZidaneEpilepsy is a neurological disorder characterized by recurrent seizures, significantly impacting the quality of life of patients. Effective detection and analysis of epileptic seizures are crucial for timely intervention and management. This paper presents the integration of a fast algorithm for epileptic seizures detection with an OLAP (Online Analytical Processing) system using a star schema data warehouse model. By leveraging … …Journal of Computer Science, Vol. 22, Issue 10 · 12 Oct 2026 · 678 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Data Mining Driven Framework for Image-Based Crop Stress Analysis Using IPCA, FP-Growth, ConvLSTM, and Sequential ModelsA. Josephine, A. SubhashiniDetecting crop stress before it becomes serious has a major impact on the food supply. It helps in avoiding the loss of crops, increases productivity and helps farmers to practice precision farming. Most technologies today are designed specifically to either detect crop stress or to predict how well the crop will grow. Many of the technologies do not combine the … …Journal of Computer Science, Vol. 22, Issue 8 · 21 Aug 2026 · 922 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis of Deep Learning Models for Multi-Step Prediction of Financial Time SeriesSaugat Aryal, Dheynoshan Nadarajah, Prabath Lakmal Rupasinghe et al.Financial time series prediction has been a key topic of interest among researchers considering the complexity of the domain and also due to its significant impact on a wide range of applications. In contrast to one-step ahead prediction, multi-step forecasting is more desirable in the industry but the task is more challenging. In recent days, advancement in deep learning has … …Journal of Computer Science, Vol. 16, Issue 10 · 27 Oct 2020 · 6,967 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Review of the Recent Advances Made in the Black-Scholes Models and Respective Solutions MethodsYasir Hamad Al Saedi, Gurudeo Anand TularamThe Black-Scholes model has been a major advance in finance over a period of time; this paper examines this model in some detail, in terms of the latest developments in both analytical and numerical solutions. The paper initially briefly examines historical aspects but quickly moves to a critical analysis of the works in the applications, solutions and implications for the … …Journal of Mathematics and Statistics, Vol. 14, Issue 1 · 8 Jan 2018 · 8,621 accessesView PDFCite
Research ArticleOpen accessIn the abstractDETECTION OF LAND USE AND LAND COVER CHANGES IN DIRAB REGION OF SAUDI ARABIA USING REMOTELY SENSED IMAGERIESR. Madugundu, K. A. Al-Gaadi, V. C. Patil, E. TolaKnowledge of Land Use and Land Cover (LULC) changes is important for many planning and management activities. It is thought to be an essential element for modeling and understanding the major land forms, especially in arid regions like Saudi Arabia. This study investigates the LULC changes in Dirab region of Saudi Arabia between 1980 and 2010, using Landsat TM/ETM+images. After … …American Journal of Environmental Sciences, Vol. 10, Issue 1 · 30 Jan 2014 · 8,013 accessesView PDFCite
Research ArticleOpen accessIn the abstractPotential Zones of Peruvanthanam and Valiyathodu Sub-Watersheds of Manimala River BasinVadakkepurakkal Rekha, Aikara Varkey George, Rita MendezGroundwater is a dynamic and replenishable natural resource. But in hard rock terrains, its availability is of limited extent. In sub-watershed studies, remote sensing and GIS techniques have the advantages of spatial, spectral and temporal data, covering large and inaccessible areas within a short span of time. Thus this technique has become a very handy tool in assessing and monitoring … …American Journal of Environmental Sciences, Vol. 9, Issue 1 · 20 Feb 2013 · 7,389 accessesView PDFCite
Research ArticleOpen accessIn the abstractNeural Network Change Detection Model for Satellite Images Using Textural and Spectral CharacteristicsA. K. Helmy, Gh. S. El-TaweelProblem statement: Change detection is the process of identifying difference of the state of an object or phenomena by observing it at different time. Essentially, it involves the ability to quantify temporal effects using multi-temporal data sets. Information about change is necessary for evaluating land cover and the management of natural resources. Approach: A neural network model based on both … …American Journal of Engineering and Applied Sciences, Vol. 3, Issue 4 · 4 Nov 2010 · 8,156 accessesView PDFCite
Research ArticleOpen accessIn the abstractAssessing the Applicability of Landslide Databases for Hazard Management Using Objective and Subjective Models: Australian Geoinformatic CaseM. OwneghProblem statement: In order to assess the applicability of Australian landslide databases as a hazard management support system, current hard and soft literature and data sources were screened. This assessment resulted in the selection of four main data bases including national landslide database (A), Peril Aus ІІ (B), the Cities project (C) and analytical study of Fell (D). Approach: In … …Current Research in Geoscience, Vol. 1, Issue 1 · 30 Jun 2010 · 10,352 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplication of MultiScale Hidden Markov Modeling Wavelet Coefficients to fMRI Activation DetectionFangyuan Nan, Yaonan Wang, Xiaoping MaProblem Statement: The problem of detection of functional magnetic resonance images (fMRIs), that is, to decide active and nonactive regions of human brain from fMRIs is studied in this paper. fMRI research is finding and will find more and more applications in diagnosing and treating brain diseases like depression and schizophrenia. At its initial stage fMRI detection are pixel-wise methods, … …Journal of Mathematics and Statistics, Vol. 4, Issue 4 · 31 Dec 2008 · 7,546 accessesView PDFCite