Deep learning techniques became crucial in analyzing satellite images for various remote sensing applications such as water body detection. Water body segmentation helps identify and analyze the statistics of various water bodies such as rivers, lakes, and reservoirs. Remote sensing-based real-time water body detection aids in providing a proper response during crises such as floods and course changes in rivers. However, the need for high-resolution multichannel satellite images is the main challenge in achieving a highly accurate water body segmentation. Most water body extraction methods described in the literature use multi-band satellite data that gather extra information from additional bands. However, the lack of such a dataset poses a significant challenge to the analysis. As a result, the research in this field is considerably weaker compared with the other related disciplines. The current study focuses on a research problem for segmenting water body regions from relatively low
Additive manufacturing or 3D printing has been on the rise and is the backbone of all major fields, such as the automotive sector, aerospace industry, sustainable construction, etc. The implementation of Artificial Intelligence (AI) for 3D printing has been the focus of research all over the world.
I sometimes see people refer to neural networks as just “another tool in your machine learning toolbox”. They have some pros and cons, they work here or there, and sometimes you can use them to win…
For the Robotic and Autonomous Systems program at University of Pennsylvania Andrew Saunders has used artificial intelligence to design a wall installation.
PRIMARY TUMOR OR METASTASIS? DEEP LEARNING AND RADIOMICS ALLOW PRECISE DIFFERENTIATION IN BRAIN TUMORS Krems (Austria), 18. January, 2023 – The distinction between primary tumors and metastases can be made quickly and accurately in brain tumors using radiomics and deep learning algorithms. This.