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

85 results for “Spatial Information”
Set a search alert
Research ArticleOpen accessIn the abstractA Multi-Modal Image Fusion Approach for Visual and Infrared Images via Shearlet-Based DecompositionApoorav Sharma, Shagun Sharma, Kalpna Guleria et al.The integration of optical lens technologies with night vision has become necessary due to the increasing demand to enhance public safety and surveillance, particularly in vulnerable areas, public transportation, and airports. Due to vision clarity issues or the lack of thermal information, conventional single-modality systems often fail to detect concealed dangers. This research presents a multimodal image fusion architecture that … …Journal of Computer Science, Vol. 22, Issue 1 · 2 Feb 2026 · 1,899 accessesView PDFCite
Research ArticleOpen accessIn the abstractSM-SCAM YOLO: Enhancing Object Detection with Multi-Scale Module and Spatial Channel Attention MechanismShanmuga Sundari Mariyappan, Kayalvizhi Mohan, K. B. K. S. DurgaDetecting tiny objects remains a significant hurdle in computer vision, primarily due to scale variation, occlusion, and the loss of detail in low-resolution features. Although YOLO-based detectors are popular for their speed and efficiency in real-time tasks, they often struggle with accurately identifying small objects because of information loss during downsampling. This study introduces an improved YOLO-based model that integrates … …Journal of Computer Science, Vol. 21, Issue 6 · 12 Jun 2025 · 3,921 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Disaster Resilience through Spatial Planning Strategies, a Case Study of Bono Region, GhanaAmponsah Maxwell, Nandi Nandi, Maryani EnokThe adverse impact of climate change has necessitated the global community to leverage spatial planning to curb the negative impacts of such incidents. Disasters continue to occur in human settlements, which makes it necessary to develop resilience through spatial planning strategies. The research question underpinning this study is, how can disaster resilience be improved through spatial planning strategies? Reducing the … …Journal of Social Sciences, Vol. 20, Issue 1 · 30 Dec 2024 · 5,008 accessesView PDFCite
Research ArticleOpen accessIn the abstractCohesion Analysis of Rubber Stand Ages Using Object-Based Image Analysis and Spatial AutocorrelationJiradech Majandang, Suepsai Prasansat, Patiwat Littidej et al.Latex and rubber wood are crucial raw materials used in various industries and play a significant role in the economies of many countries, particularly in tropical regions. Mapping the areas where these materials are planted and classifying the age of rubber stands is important for managing growth assessment, yield assessment, and estimating the number of mature rubber trees that will … …Journal of Computer Science, Vol. 20, Issue 12 · 29 Nov 2024 · 5,293 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnalysis of Areas Susceptible to Gullies in Ideato South Local Government Area of Nigeria Using Geographic Information System and Remote Sensing TechnologySylvanus IroGully erosion is a critical environmental hazard in Southeastern Nigeria, threatening agricultural productivity, infrastructure, and communal safety. This study provides a spatially explicit assessment of gully erosion susceptibility in Ideato South Local Government Area (LGA), Imo State, using an integrated Geographic Information System (GIS) and Remote Sensing framework. The methodology employed a multi-criteria decision-making approach, utilizing the Analytical Hierarchy Process … …American Journal of Environmental Sciences, Vol. 22, Issue 1 · 20 Jul 2026 · 1,189 accessesView PDFCite
Research ArticleOpen accessIn the abstractLT-LBP-Based Spatial Texture Feature Extraction with Deep Learning for X-Ray ImagesPankaja Lakshmi P., Sivagami M.The novel logarithmic transformation of Local Binary Pattern (LT-LBP) for texture feature extraction is used with Deep Learning (DL) models. The Computational complexity in the DL models asymptotically increases with the data sesssst and the depth of the layers in Convolutional Neural Networks (CNN). Pre-processing the images before training the DL model holds a strong impact on the operation speed … …Journal of Computer Science, Vol. 20, Issue 1 · 18 Dec 2023 · 7,190 accessesView PDFCite
Research ArticleOpen accessIn the abstractAssessment of Soil Loss Using GIS and RUSLE Model in Bakiya River Basin (BRB), Central NepalSujan Bista, Naresh Kazi Tamrakar, Kishor Rimal, Arju BhattaraiSoil erosion is the major geological hazard in the fragile landscape of Sub-Himalaya. This study examines the susceptibility of the Bakiya River Basin (BRB) in Central Nepal to soil erosion because of its steep topography, fragile geology, the impact of intense monsoon rainfall, and the lack of a direct monitoring mechanism available for rainfall-runoff. This study examines the spatial variations … …Current Research in Geoscience, Vol. 14, Issue 1 · 20 Oct 2025 · 3,384 accessesView PDFCite
Review ArticleOpen accessIn the abstractAssessment of Dust Event By RS, GIS, MODIS and Statistical Methods Among Satellite ImagesKaveh Ostad-Ali-Askari, Naimeh Rahimi, Parisa Ashrafi et al.Dust is an event that occurs in most sections of the world that leads to financial loss and harmful environmental impacts. Several factors are included in dust event incidence, some of them are natural and others are due to human processes and their impact on the environment. Thus, very critical situations are coming and it is expected that the majority … …American Journal of Engineering and Applied Sciences, Vol. 14, Issue 2 · 25 Jun 2021 · 6,698 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid CNN-Based Transformer Pipeline With Radiomic Fusion for Multi-Class Lung Cancer DetectionAanchal Vij, Kuldeep Singh Kaswan, Anand NayyarEarly detection of lung cancer remains challenging due to high intra-class variation and inter-class similarity in Computed Tomography (CT) images. In this paper, we propose a hybrid deep learning model that combines convolutional, attention-based, and transformer-guided representations to address these challenges in multi-class lung cancer classification. For deep feature extraction, we use the EfficientNetV2-S architecture augmented with a Convolutional Block … …Journal of Computer Science, Vol. 22, Issue 6 · 3 Jun 2026 · 1,528 accessesView PDFCite
Research ArticleOpen accessIn the abstractCPF-Net: Cross-modal CT and Pathology Guided Feature Learning for CT-based Lung Cancer Subtype ClassificationPeizhi Tan, Debiao YanAccurate classification of lung cancer subtypes from CT images remains challenging due to the subtle radiological differences between adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC). We propose CPF-Net, a deep learning framework that integrates CT and pathological information through a Linear Spatial Reduction Attention (LSRA) module. The framework processes whole slide images using a modified CTransPath architecture for pathological feature … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 3 · 23 Jan 2026 · 1,856 accessesView PDFCite