Zobrazeno 1 - 10
of 37
pro vyhledávání: '"Szemenyei, Márton"'
Skin cancer is a frequently occurring cancer in the human population, and it is very important to be able to diagnose malignant tumors in the body early. Lesion segmentation is crucial for monitoring the morphological changes of skin lesions, extract
Externí odkaz:
http://arxiv.org/abs/2309.01072
Imitation Learning uses the demonstrations of an expert to uncover the optimal policy and it is suitable for real-world robotics tasks as well. In this case, however, the training of the agent is carried out in a simulation environment due to safety,
Externí odkaz:
http://arxiv.org/abs/2206.10797
Publikováno v:
In Cleaner Environmental Systems June 2024 13
Reliable segmentation of retinal vessels can be employed as a way of monitoring and diagnosing certain diseases, such as diabetes and hypertension, as they affect the retinal vascular structure. In this work, we propose the Residual Spatial Attention
Externí odkaz:
http://arxiv.org/abs/2009.08829
Retinal vessel segmentation is a vital step for the diagnosis of many early eye-related diseases. In this work, we propose a new deep learning model, namely Channel Attention Residual U-Net (CAR-UNet), to accurately segment retinal vascular and non-v
Externí odkaz:
http://arxiv.org/abs/2004.03702
The precise segmentation of retinal blood vessels is of great significance for early diagnosis of eye-related diseases such as diabetes and hypertension. In this work, we propose a lightweight network named Spatial Attention U-Net (SA-UNet) that does
Externí odkaz:
http://arxiv.org/abs/2004.03696
Retinal vessel segmentation plays an imaportant role in the field of retinal image analysis because changes in retinal vascular structure can aid in the diagnosis of diseases such as hypertension and diabetes. In recent research, numerous successful
Externí odkaz:
http://arxiv.org/abs/2004.03697
Deep Learning has become exceptionally popular in the last few years due to its success in computer vision and other fields of AI. However, deep neural networks are computationally expensive, which limits their application in low power embedded syste
Externí odkaz:
http://arxiv.org/abs/1910.10949
Autor:
Reizinger, Patrik, Szemenyei, Márton
Reinforcement Learning enables to train an agent via interaction with the environment. However, in the majority of real-world scenarios, the extrinsic feedback is sparse or not sufficient, thus intrinsic reward formulations are needed to successfully
Externí odkaz:
http://arxiv.org/abs/1910.10840
Autor:
Princz-Jakovics, Tibor1 (AUTHOR) princz-jakovics.tibor@gtk.bme.hu, Szemenyei, Márton2 (AUTHOR)
Publikováno v:
Environment Systems & Decisions. Dec2024, Vol. 44 Issue 4, p763-778. 16p.