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 Weak Supervision in Enemy Detection Based on Computer Game Output Video Stream(Wydawnictwo Politechniki Łódzkiej, 2023) Rajtar, Jakub; Szajerman, DominikThis work contains a solution for image classification and enemy detection in the output video stream of a computer game. Weak supervision was used to achieve the goal. It shows that an image dataset with a certain number of incorrect classification labels can be used to correctly build a classification model that distinguishes between images containing and not containing an enemy. Based on the results of such classification stage and the use of class activation maps, a method for detecting enemies on positively classified images was proposed. The tedious process of image labeling, which is necessary for supervised learning, does not occur here.Pozycja Transformers Neural Networks Applications in Different Computer Vision Tasks(Wydawnictwo Politechniki Łódzkiej, 2023) Brodzicki, Andrzej; Piekarski, Michał; Kostuch, Aleksander; Noworolnik, Filip; Aleksandrowicz, Maciej; Wójcicka, Anna; Jaworek-Korjakowska, JoannaTransformers architectures are one of the latest inventions in the field of deep learning. Originally dedicated to NLP, they begin to find use in computer vision too. In this paper, we briefly describe the idea behind vision transformers and present a few examples, where we utilised them in our research, focusing on the field of medical images and autonomous driving. We show, that vision transformers can be used in various tasks, such as detection or classification, as well as explain how some of their drawbacks can be mitigated with a transfer learning approach.Pozycja Challenges of Crop Classification from Satellite Imagery with Eurocrops Dataset(Wydawnictwo Politechniki Łódzkiej, 2023) Aszkowski, Przemysław; Kraft, MarekCrops monitoring and classification on a nationwide level provide important information for sustainable agricultural management, food security, and policy-making. Recent technological advancements, followed by Earth observation programmes like Copernicus, have provided plenty of publicly available multispectral data. Combining these data with field annotations allows for continuous crop monitoring from publicly available data. In this paper, we present a solution for crop classification to determine crop type from Sentinel-2 multispectral data, utilizing machine learning techniques. Apart from presenting initial results, we discuss the challenges of crop classification on a Eurocrops dataset and further research directions.Pozycja Progress in Polish Artificial Intelligence Research 4(Wydawnictwo Politechniki Łódzkiej, 2023) Wojciechowski, Adam (Ed.); Lipiński, Piotr (Ed.)