Zobrazeno 1 - 10
of 385
pro vyhledávání: '"Hansen Lasse"'
Autor:
Keuth, Ron, Hansen, Lasse, Balks, Maren, Jäger, Ronja, Schröder, Anne-Nele, Tüshaus, Ludger, Heinrich, Mattias
Semantic segmentation is a crucial task in medical imaging. Although supervised learning techniques have proven to be effective in performing this task, they heavily depend on large amounts of annotated training data. The recently introduced Segment
Externí odkaz:
http://arxiv.org/abs/2411.12602
Autor:
Bockelmann Niclas, Graßhoff Jan, Hansen Lasse, Bellani Giacomo, Heinrich Mattias P., Rostalski Philipp
Publikováno v:
Current Directions in Biomedical Engineering, Vol 5, Iss 1, Pp 17-20 (2019)
The electrical activity of the diaphragm (EAdi) is a novel monitoring parameter for patients under assisted ventilation and is used for assessing the patient’s neural respiratory drive. It is recorded by an array of electrodes placed inside the eso
Externí odkaz:
https://doaj.org/article/13a0b43939d44e58b96eb18f93a1cddf
Autor:
Keuth, Ron, Hansen, Lasse, Balks, Maren, Jäger, Ronja, Schröder, Anne-Nele, Tüshaus, Ludger, Heinrich, Mattias
Purpose: Semantic segmentation and landmark detection are fundamental tasks of medical image processing, facilitating further analysis of anatomical objects. Although deep learning-based pixel-wise classification has set a new-state-of-the-art for se
Externí odkaz:
http://arxiv.org/abs/2405.19746
Autor:
Hansen, Lasse Hyldig, Andersen, Nikolaj, Gallifant, Jack, McCoy, Liam G., Stone, James K, Izath, Nura, Aguirre-Jerez, Marcela, Bitterman, Danielle S, Gichoya, Judy, Celi, Leo Anthony
Background Advancements in Large Language Models (LLMs) hold transformative potential in healthcare, however, recent work has raised concern about the tendency of these models to produce outputs that display racial or gender biases. Although training
Externí odkaz:
http://arxiv.org/abs/2405.05049
Autor:
Hansen, Lasse H., Jensen, Simon B., Philipsen, Mark P., Møgelmose, Andreas, Bodum, Lars, Moeslund, Thomas B.
Identifying and classifying underground utilities is an important task for efficient and effective urban planning and infrastructure maintenance. We present OpenTrench3D, a novel and comprehensive 3D Semantic Segmentation point cloud dataset, designe
Externí odkaz:
http://arxiv.org/abs/2404.07711
Autor:
McDermott, Matthew B. A., Hansen, Lasse Hyldig, Zhang, Haoran, Angelotti, Giovanni, Gallifant, Jack
In machine learning (ML), a widespread adage is that the area under the precision-recall curve (AUPRC) is a superior metric for model comparison to the area under the receiver operating characteristic (AUROC) for binary classification tasks with clas
Externí odkaz:
http://arxiv.org/abs/2401.06091
Autor:
Enevoldsen, Kenneth, Hansen, Lasse, Nielsen, Dan S., Egebæk, Rasmus A. F., Holm, Søren V., Nielsen, Martin C., Bernstorff, Martin, Larsen, Rasmus, Jørgensen, Peter B., Højmark-Bertelsen, Malte, Vahlstrup, Peter B., Møldrup-Dalum, Per, Nielbo, Kristoffer
Large language models, sometimes referred to as foundation models, have transformed multiple fields of research. However, smaller languages risk falling behind due to high training costs and small incentives for large companies to train these models.
Externí odkaz:
http://arxiv.org/abs/2311.07264
Synthetic data serves as an alternative in training machine learning models, particularly when real-world data is limited or inaccessible. However, ensuring that synthetic data mirrors the complex nuances of real-world data is a challenging task. Thi
Externí odkaz:
http://arxiv.org/abs/2310.16981
State-of-the-art deep learning-based registration methods employ three different learning strategies: supervised learning, which requires costly manual annotations, unsupervised learning, which heavily relies on hand-crafted similarity metrics design
Externí odkaz:
http://arxiv.org/abs/2306.16997
Autor:
Eisenmann, Matthias, Reinke, Annika, Weru, Vivienn, Tizabi, Minu Dietlinde, Isensee, Fabian, Adler, Tim J., Ali, Sharib, Andrearczyk, Vincent, Aubreville, Marc, Baid, Ujjwal, Bakas, Spyridon, Balu, Niranjan, Bano, Sophia, Bernal, Jorge, Bodenstedt, Sebastian, Casella, Alessandro, Cheplygina, Veronika, Daum, Marie, de Bruijne, Marleen, Depeursinge, Adrien, Dorent, Reuben, Egger, Jan, Ellis, David G., Engelhardt, Sandy, Ganz, Melanie, Ghatwary, Noha, Girard, Gabriel, Godau, Patrick, Gupta, Anubha, Hansen, Lasse, Harada, Kanako, Heinrich, Mattias, Heller, Nicholas, Hering, Alessa, Huaulmé, Arnaud, Jannin, Pierre, Kavur, Ali Emre, Kodym, Oldřich, Kozubek, Michal, Li, Jianning, Li, Hongwei, Ma, Jun, Martín-Isla, Carlos, Menze, Bjoern, Noble, Alison, Oreiller, Valentin, Padoy, Nicolas, Pati, Sarthak, Payette, Kelly, Rädsch, Tim, Rafael-Patiño, Jonathan, Bawa, Vivek Singh, Speidel, Stefanie, Sudre, Carole H., van Wijnen, Kimberlin, Wagner, Martin, Wei, Donglai, Yamlahi, Amine, Yap, Moi Hoon, Yuan, Chun, Zenk, Maximilian, Zia, Aneeq, Zimmerer, David, Aydogan, Dogu Baran, Bhattarai, Binod, Bloch, Louise, Brüngel, Raphael, Cho, Jihoon, Choi, Chanyeol, Dou, Qi, Ezhov, Ivan, Friedrich, Christoph M., Fuller, Clifton, Gaire, Rebati Raman, Galdran, Adrian, Faura, Álvaro García, Grammatikopoulou, Maria, Hong, SeulGi, Jahanifar, Mostafa, Jang, Ikbeom, Kadkhodamohammadi, Abdolrahim, Kang, Inha, Kofler, Florian, Kondo, Satoshi, Kuijf, Hugo, Li, Mingxing, Luu, Minh Huan, Martinčič, Tomaž, Morais, Pedro, Naser, Mohamed A., Oliveira, Bruno, Owen, David, Pang, Subeen, Park, Jinah, Park, Sung-Hong, Płotka, Szymon, Puybareau, Elodie, Rajpoot, Nasir, Ryu, Kanghyun, Saeed, Numan, Shephard, Adam, Shi, Pengcheng, Štepec, Dejan, Subedi, Ronast, Tochon, Guillaume, Torres, Helena R., Urien, Helene, Vilaça, João L., Wahid, Kareem Abdul, Wang, Haojie, Wang, Jiacheng, Wang, Liansheng, Wang, Xiyue, Wiestler, Benedikt, Wodzinski, Marek, Xia, Fangfang, Xie, Juanying, Xiong, Zhiwei, Yang, Sen, Yang, Yanwu, Zhao, Zixuan, Maier-Hein, Klaus, Jäger, Paul F., Kopp-Schneider, Annette, Maier-Hein, Lena
International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really
Externí odkaz:
http://arxiv.org/abs/2303.17719