Wydawnictwa Uczelniane / TUL Press
Stały URI zbioruhttp://hdl.handle.net/11652/17
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Pozycja Supporting Surgical Training with the Help of Computer Vision and Machine Learning Methods(Wydawnictwo Politechniki Łódzkiej, 2023) Forczmański, Paweł; Ryder, Yoonhee C; Mott, Nicole M; Gross, Christopher L.; Yu, Joon B.; Rooney, Deborah M.; Jeffcoach, David R.; Bidwell, Serena; Anidi, Chioma; Rosenthal, Lindsay; Kim, Grace J.The paper presents a novel concept of laparoscopic skills evaluation based on the automated analysis of videos recorded during simulationbased training exercises via an artificial intelligence algorithm. It has been tested on data collected during the training of actual surgeons. Its performance is promising, providing an opportunity to build an automatic system used mainly in developing countries.Pozycja Spotting Advertisements from Above: Billboard Detection and Segmentation in UAV Imagery(Wydawnictwo Politechniki Łódzkiej, 2023) Ptak, Bartosz; Dominiak, Jan; Kraft, MarekIn this work, deep-learning methods were researched for billboard detection in urban environments. Billboards are one of the adversarial visual pollutants occurring in cities, causing over-saturation of visual stimulation. Due to this, we develop an algorithm that helps in the analysis and management of urban space. We utilise near real-time object detection methods to detect and segment them on images registered by unmanned aerial vehicles (UAVs). Research is based on recent algorithms from the YOLO family with modified heads for the instance segmentation task. We gathered images and prepared hand-annotated labels for training and evaluation purposes of deep learning approaches. We reached the mAP@0.5 metric of 0.61 for detection and 0.60 for segmentation, enabling us to develop smart city applications.