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18 results for “Multi-Spectral”
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Research ArticleOpen accessEvery word in the titlePerformance Analysis of Multi Spectral Band Image Compression using Discrete Wavelet TransformR. Kousalyadevi, S. S. RamakrishnanProblem statement: Efficient and effective utilization of transmission bandwidth and storage capacity have been a core area of research for remote sensing images. Hence image compression is required for multi-band satellite imagery. In addition, image quality is also an important factor after compression and reconstruction. Approach: In this investigation, the discrete wavelet transform is used to compress the Landsat5 agriculture … …Journal of Computer Science, Vol. 8, Issue 5 · 6 Mar 2012 · 7,041 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA New Disease Index Based on Multi-Spectra of UAV to Estimate Cotton DiseaseBing Chen, Jing Wang, Qiong Wang et al.Verticillium wilt is a significant disease that affects cotton plants, which can lead to stunted growth and reduced yield. To address this, a multi-spectral comprehensive monitoring disease index model is developed using an Unmanned Aerial Vehicle (UAV) to monitor the severity of cotton Verticillium wilt. First, multi-spectral dates were collected from Hexacopter (HY-6X) and the phenotype disease grade of cotton … …American Journal of Biochemistry and Biotechnology, Vol. 19, Issue 4 · 25 Mar 2024 · 5,087 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 abstractNeurofeedback Therapy Meets Transformers: Rewiring Sleep Disorders Through AI-Driven EEG ModulationAmala Ann KA, Vaidhehi VSleep disorders such as insomnia, sleep Apnea, and hypersomnia significantly impair neurophysiological functioning, yet conventional treatments like Cognitive Behavioral Therapy for Insomnia (CBT-I) remain resource-intensive and difficult to personalize. This study introduces a novel AI-powered neurofeedback simulation framework designed to detect dysregulated EEG frequency band activity across sleep stages and simulate targeted interventions. A Transformer-based model serves as the core … …Journal of Computer Science, Vol. 22, Issue 2 · 3 Mar 2026 · 1,674 accessesView PDFCite
Research ArticleOpen accessIn the abstractXAI_MLPCNN: A Novel Explainable AI-Based Deep Learning Framework for Stress IdentificationFateh Bahadur Kunwar, Rakesh Kumar Yadav, Hitendra Singh, Nitin TripathiOver the past ten years, there has been a lot of emphasis focusedon the development of Artificial Intelligence (AI) and Machine Learning(ML)-based mental health treatments. To increase practitioners' and patients'trust in AI applications, AI systems need to explain their actions. This iscalled Explainable AI (XAI). While significant progress has been achievedin stress prediction models, XAI has not advanced as much. … …Journal of Computer Science, Vol. 21, Issue 5 · 6 May 2025 · 6,161 accessesView PDFCite
Research ArticleOpen accessIn the abstractBeatbox Classification to Distinguish User Experiences Using Machine Learning ApproachesJason Martanto, Iman Herwidiana KartowisastroResearch regarding beatbox classification has generated a relatively significant growth in the past decade. Although the differences between contributors’ expertise within a vocal percussion dataset have been mentioned in previous works, the impact of those discrepancies has not been thoroughly investigated. In this study, the authors explore performances of machine learning algorithms for beatbox classification, with an emphasis on prior … …Journal of Computer Science, Vol. 21, Issue 4 · 18 Mar 2025 · 5,208 accessesView PDFCite
Research ArticleOpen accessIn the abstractA FRAMEWORK FOR MULTILINGUAL TEXT- INDEPENDENT SPEAKER IDENTIFICATION SYSTEMSundaradhas Selva Nidhyananthan, Ramapackiam Shantha Selva KumariThis article evaluates the performance of Extreme Learning Machine (ELM) and Gaussian Mixture Model (GMM) in the context of text independent Multi lingual speaker identification for recorded and synthesized speeches. The type and number of filters in the filter bank, number of samples in each frame of the speech signal and fusion of model scores play a vital role in … …Journal of Computer Science, Vol. 10, Issue 1 · 13 Nov 2013 · 7,274 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