Internet technology and mobile technology have enabled producing and diffusing massive data sets concerning almost every aspect of day-by-day life. Remarkable examples are social media and apps for volunteered information production, as well as Open...
Drone imagery is becoming the main source of overhead information to support decisions in many different fields, especially with deep learning integration. Datasets to train object detection and semantic segmentation models to solve geospatial data a...
Background: Oral cancer is one of the most prevalent cancers worldwide. Despite that the oral cavity is easily accessible for clinical examinations, oral cancers are often not promptly diagnosed. Furthermore, to date no effective biomarkers are avail...
The possibility offered by the current technology to collect and store data sets regarding public places located on the Earth globe is posing new challenges, as far as the integration of these data sets is concerned. Analysts usually need to perform...
Background: Dendritic cells (DCs) play an important role as a bridge between innate and adaptive immunity, and changes in gene expression of DCs during the immune response to Mycobacterium tuberculosis (M.tb) may affect the development of tuberculosi...
Several geospatial studies and applications require comprehensive semantic information from points-of-interest (POIs). However, this information is frequently dispersed across different collaborative mapping platforms. Surprisingly, there is still a...
Land cover is important for global change studies, and its accuracy and reliability are usually verified by field sampling, which costs a lot. A method was proposed for the verification of land cover datasets with the geo-tagged natural scene images...
Background: Breast ductal carcinoma in situ (DCIS), a common precursor of breast cancer, has poorly understood susceptible driver genes. This study aimed to identify genes influencing DCIS progression by integrating Mendelian randomization (MR) and G...
The stable flight of drones relies on Global Navigation Satellite Systems (GNSS). However, in complex environments, GNSS signals are prone to interference, leading to flight instability. Inspired by cross-view machine learning, this paper introduces...
Object geo-localization from images is crucial to many applications such as land surveying, self-driving, and asset management. Current visual object geo-localization algorithms suffer from hardware limitations and impractical assumptions limiting th...
The limited availability of structured and consistent health-facility information poses challenges for assessing service accessibility and quality in rapidly growing cities, particularly in the Middle East. Although digital map platforms provide exte...
Plane geometry problem solving has been a long-term challenge in mathematical reasoning and symbolic artificial intelligence. With the continued advancement of automated methods, the need for large-scale datasets and rigorous evaluation frameworks ha...
The application of contemporary artificial intelligence techniques to address geometric problems and automated deductive proofs has always been a grand challenge to the interdisciplinary field of mathematics and artificial intelligence. This is the f...
Recently, open-domain question-answering systems have achieved tremendous progress because of developments in large language models (LLMs), and have successfully been applied to question-answering (QA) systems, or Chatbots. However, there has been li...
Automatic geometric problem-solving is an active and challenging subfield at the intersection of AI and mathematics, where geometric problem parsing plays a critical role. It involves converting geometric diagram and text into certain formal language...
The Singular Value Decomposition (SVD) is a mathematical procedure with multiple applications in the geosciences. For instance, it is used in dimensionality reduction and as a support operator for various analytical tasks applicable to spatio-tempora...
This research reports the ongoing design of the HISMACITY (Historical Small Smart City) Protocol, a planning tool with a certification system. The tool is designed for small municipalities in Europe. Through the award-winning certification system, th...
Image-based geo-localization focuses on predicting the geographic information of query images by matching them with annotated images in a database. To facilitate relevant studies, researchers collect numerous images to build the datasets, which explo...
Background: JianPiYiFei (JPYF) II granules are a Chinese medicine for the treatment of chronic obstructive pulmonary disease (COPD). However, the main components and underlying mechanisms of JPYF II granules are not well understood. This study aimed...
Background: Personalizing adjuvant chemotherapy (ACT) after curative resection in early-stage NSCLC remains unmet because prior ACT-biomarker findings rarely reproduce across studies. Key barriers are platform and preprocessing heterogeneity, dominan...
Abstract: Flooding is one of the most frequent natural disasters across the world, which damages properties and may take the lives of people. Flood warning systems can play a significant role in minimizing those effects by helping to evacuate people...
Detection and Semantic Segmentation of vehicles in drone aerial orthomosaics has applications in a variety of fields such as security, traffic and parking management, urban planning, logistics, and transportation, among many others. This paper presen...
Accurate and detailed spatial data on wind energy infrastructure is essential for renewable energy planning, grid integration, and system analysis. However, publicly available datasets often suffer from limited spatial accuracy, missing attributes, a...
UAVs typically rely on satellite navigation for positioning, yet this method proves ineffective in instances where the signal is inadequate or communication is disrupted. Visually based positioning technology has emerged as a reliable alternative. In...
In order to improve the observation capability in one of the most active volcanic areas in the world, Mt. Etna, we developed a processing method to use the surveillance cameras for a quasi real-time mapping of syn-eruptive processes. Following an eva...
Third-generation geostationary meteorological satellites (GEOs), such as Himawari-8/9 Advanced Himawari Imager (AHI), Geostationary Operational Environmental Satellites (GOES)-R Series Advanced Baseline Imager (ABI), and Meteosat Third Generation (MT...
Modern convolutional neural networks (CNNs) are often trained on pre-set data sets with a fixed size. As for the large-scale applications of satellite images, for example, global or regional mappings, these images are collected incrementally by multi...
The editorial team of the journal IJGI would like to make the following corrections to the published paper [1]:[...]
Data literacy is an essential skill for today’s digital way of life, to be able to judge the reliability of different data presented, for instance in news and media or in business processes. Geo-Spatial data are a specific kind of data and infl...
Deep Learning algorithms are becoming common in solving different supervised and unsupervised learning problems. Different deep learning algorithms were developed in last decade to solve different learning problems in different domains such as comput...
Recent approaches to geo-referencing X posts have focused on the use of language modelling techniques that learn geographic region-specific language and use this to infer geographic coordinates from text. These approaches rely on large amounts of lab...
The ever-increasing availability of linked open geospatial data provides an unprecedented source of geo-information to describe urban environments. This wealth of data should be turned into actionable knowledge: for example, open data could be used a...
The increasing availability of satellite imagery acquired by existing and new sensors allows a wide variety of new applications that depend on the use of diverse spectral and spatial resolution data sets. One of the pre-conditions for the use of hybr...
The accurate prediction of underground formation lithology class and tops is a critical challenge in the oil industry. This paper presents a machine-learning (ML) approach to predict lithology from drilling data, offering real-time litho-facies ident...
Due to the large difference between normal conditions and damaged road images, geo-location in damaged areas often fails due to occlusion or damage to buildings and iconic signage in the image. In order to study the influence of post-war building and...
Topographic databases maintained by national mapping agencies are currently the most common nationwide data sets in geo-information. The application of laser scanning as source data for surveying is increasing. Along with this development, several an...
This paper reviews the current GeoAI and machine learning applications in hydrological and hydraulic modeling, hydrological optimization problems, water quality modeling, and fluvial geomorphic and morphodynamic mapping. GeoAI effectively harnesses t...
The increasing availability of linked data poses new challenges for the identification and retrieval of the most appropriate data sources that meet user needs. Recent dataset catalogs and recommenders provide advanced methods that facilitate linked d...
Understanding human mobility patterns is of great importance for urban planning, traffic management, and even marketing campaign. However, the capability of capturing detailed human movements with fine-grained spatial and temporal granularity is stil...
(1) Background: Acute myeloid leukemia (AML) is a clonal malignancy with heterogeneity in genomics and clinical outcome. Metabolism reprogramming has been increasingly recognized to play an important role in the leukemogenesis and prognosis in AML. A...
2 June 2020
Clear cell carcinoma of the ovary (ovarian clear cell carcinoma (OCCC)) is one epithelial ovarian carcinoma that is known to have a poor prognosis and a tendency for being refractory to treatment due to unclear pathogenesis. Published investigations...
GASAKe is an empirical-hydrological model aimed at forecasting the time of occurrence of landslides. Activations can be predicted of either single landslides or sets of slope movements of the same type in a homogeneous environment. The model requires...
Privacy Preserving and Anonymity have gained significant concern from the big data perspective. We have the view that the forthcoming frameworks and theories will establish several solutions for privacy protection. The k-anonymity is considered a key...
Background/Objectives: The precise classification of non-small-cell lung cancer (NSCLC) into lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) has important role in treatment decisions and in prognosis. Proper subtyping ensures that...
Geospatial information plays an important role in environmental modelling, resource management, business operations, and government policy. However, very little or no commonality between formats of various geospatial data has led to difficulties in u...
In this data description, we introduce a unique (geo)dataset with publicly available information about the municipalities focused on (geo)participatory aspects of local administration. The dataset comprises 6258 Czech municipalities linked with their...
Small molecular networks within complex pathways are defined as subpathways. The identification of patient-specific subpathways can reveal the etiology of cancer and guide the development of personalized therapeutic strategies. The dysfunction of sub...
A comprehensive understanding of environmental changes taking place in coastal regions relies on accurate integration of both terrestrial and submerged geo-environmental datasets. However, this practice is hardly implemented because of the high (or e...
This study proposes a systematic framework for establishing ethical guidelines for GeoAI (Geospatial Artificial Intelligence), which integrates AI with spatial data science, GIS, and remote sensing. While general AI ethics have advanced through the O...
The vulnerability of economies and the associated familiar lifestyles have led to numerous policy measures in Europe. The proposed Critical Raw Materials Act (CRMA) sets indicative targets for 2030. A sustainable change in the supply situation requir...
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