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Detecting feature requests of 3rd-party developers via machine learning: A case study of the SAP Community
Researchers from the Technical University of Munich, University of Innsbruck and SAP Deutschland set out to test whether the use of supervised machine learning models can be an effective means for the identification of feature requests.
Real-time segmentation of desiccation cracks onboard UAVs for planetary exploration
Researchers from Queensland University of Technology studied the use of Unmanned Aerial Vehicles (UAVs) to detect and highlight areas with desiccation cracks for closer inspection to look for habitable environments and traces of life (biosignatures).
An AI-based computer-aided system for better knee osteoarthritis assessment
Researchers from the Medical University of Graz recently collaborated to analyze the impact of an artificial intelligence (AI)-based computer system on the accuracy and agreement rate of board-certified orthopedic surgeons to detect X-ray features indicative of knee OA (osteoarthritis assessment).
Lightweight multi-drone detection and 3D-localization via YOLO
Researchers from Indian Institute of Technology Kanpur recently evaluated a method to perform real-time multiple drone detection and three-dimensional localization using state-of-the-art tiny-YOLOv4 object detection algorithm and stereo triangulation.
Automated detection of malaria parasites using convolutional neural networks
Researchers from Imperial College London recently focused on developing an automated image analysis method to improve accuracy and standardization of smear inspection that retains capacity for expert confirmation and image archiving.
Automated segmentation of cervical anatomy to interrogate preterm birth
Researchers from Columbia University are finding ways to develop a computational tool developed to better segment the entire cross-sectional area of the cervix tissue from 2D transvaginal ultrasounds, enabling the creation of a generalizable, cervical-features-based prediction model of PTB risk.