Special Issue "GeoAI: Integration of Artificial Intelligence, Machine Learning and Deep Learning with GIS"
Deadline for manuscript submissions: 31 December 2020.
Interests: smart mining; renewables in mining; space mining; AICBM (AI, IoT, cloud, big data, mobile) convergence; unmanned aerial vehicle; mine planning and design; open-pit mining operation; mine safety; geographic information systems; 3D geo-modeling; geostatistics; hydrological analysis; energy analysis and simulation; design of solar energy conversion systems; renewable energy systems
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Special Issue in Minerals: Applications of Unmanned Aerial Vehicle and Artificial Intelligence Technologies in Mining from Exploration to Reclamation
Special Issue in Applied Sciences: Recent Advances in Smart Mining Technology
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Special Issue in Applied Sciences: Renewable Energy Systems: Optimal Planning and Design
The field of Artificial Intelligence (AI), including machine learning and deep learning, has developed rapidly in recent years and has been spreading across all industries so that innovative changes are taking place in the industrial field through the combination of AI and domain knowledge.
This change is also having a significant impact on geographic information systems (GIS). Machine learning has been a core component of spatial analysis in GIS for classification, clustering, and prediction. In addition, deep learning is being integrated with GIS to automatically extract useful information from satellite, aerial or drone imagery by means of image classification, object detection, semantic and instance segmentation, etc. The integration of AI, machine learning, and deep learning with GIS has developed into the concept of a “Geospatial Artificial Intelligence (GeoAI)” that is a new paradigm for geographic knowledge discovery and beyond.
This Special Issue (SI) encourages scientists, engineers, educators, students, and researchers to address the current state-of-the-art in GeoAI. Original research contributions and reviews providing examples of AI, machine learning, and deep learning techniques used in GIS can be included in this SI.Prof. Dr. Yosoon Choi
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- Geospatial artificial intelligence
- Machine learning in GIS
- Deep learning in GIS
- Spatial prediction
- Spatial interpolation
- Object detection
- Semantic segmentation
- Instance segmentation