Improving spleen segmentation in ultrasound images using a hybrid deep learning framework by Ali Karimi, Javad Seraj, Fatemeh Mirzadeh Sarcheshmeh, Kasra Fazli, Amirali Seraj, Parisa Eslami, Mohamadreza Khanmohamadi, Helia Sajjadian Moosavi, Hadi Ghattan Kashani, Abdoulreza Sajjadian Moosavi, Masoud Shariat Panahi

“…Specifically, our approach achieved a mean Intersection over Union (mIoU) of 94.17% and a mean Dice (mDice) score of 96.82%, surpassing models such as Splenomegaly Segmentation Network (SSNet), U-Net, and Variational autoencoder based methods. …”
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Steel surface defect detection and segmentation using deep neural networks by Sara Ashrafi, Sobhan Teymouri, Sepideh Etaati, Javad Khoramdel, Yasamin Borhani, Esmaeil Najafi

“…Based on the obtained results, the U-Net model with pre-trained backbones achieves a Dice Similarity Coefficient of 72%, outperforming existing methods. …”
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Promote Renewable Energies Efficiently and Effectively by Arbeitsgruppe „Energiesysteme der Zukunft“, Justus Haucap, Jürgen Kühling, Munib Amin, Gert Brunekreeft, Dörte Fouquet, Veronika Grimm, Jörg Gundel, Martin Kment, Wolfgang Ketter, Jochen Kreusel, Charlotte Kreuter-Kirchhof, Mario Liebensteiner, Albert Moser, Marion Ott, Christian Rehtanz, Heike Wetzel, Jonathan Meinhof, Marlene Wagner, Miriam Borgmann, Cyril Stephanos

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Accuracy of an articulated head-and-neck motion model using deep learning-based instance segmentation of skeletal bones in CT scans for image registration in radiotherapy by Alexandra Walter, Cornelius J. Bauer, Ama Katseena Yawson, Philipp Hoegen-Saßmannshausen, Sebastian Adeberg, Jürgen Debus, Oliver Jäkel, Martin Frank, Kristina Giske

“…Both sets of segmentations are evaluated using DICE, Hausdorff Distance and surface DICE. We investigate their impact on the build-up of the biomechanical articulated skeleton model by deviations in joint positioning and CT-CT registration accuracy using target registration error (TRE). …”
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Machine Learning-Based Normal White Blood Cell Multi-Classification Optimization by Taeyeon Gil, Sukjun Lee, Onseok Lee

“…The nucleus showed high segmentation performance with an average accuracy of 98.58% and a Dice coefficient of 0.9233, whereas the cells achieved an average accuracy of 99.47% and a Dice coefficient of 0.9324. …”
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An Attention-Based Residual U-Net for Tumour Segmentation Using Multi-Modal MRI Brain Images by Najme Zehra Naqvi, K. R. Seeja

“…For BraTS 2020 it achieved Dice Coefficient of 0.9978, 0.9378 and 0.9478 for WT (Whole tumour), TC (Tumour core), and ET (Enhancing Tumour) respectively and for BraTS 2018 it achieved Dice Coefficient 98.32, 93.32 and 92.32 for WT (Whole tumour), TC (Tumour core), and ET (Enhancing Tumour) respectively.…”
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A Novel Network for Choroidal Segmentation Based on Enhanced Boundary Information by Wenbo Huang, Chaofan Qu, Yang Yan

“…The BENet architecture achieved a Dice coefficient of 95.24%, a Hausdorff distance of 2.68, and an accuracy of 99.12%. …”
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Alasdair MacIntyre: relatividad conceptual, tomismo y liberalismo by Carlos Isler S.

“…Se expone esta teoría y se analiza su compatibilidad con el tomismo, tradición a la que MacIntyre dice pertenecer, y con el liberalismo, tradición a la que critica con vigor.…”
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Sacar la voz by Valentina Bulo

“… Efectivamente para sacar la voz debemos estar dispuestos de algún modo, debemos situarnos, pararnos en el mundo de una manera tal que la voz salga casi como evaporación, soplo, como la larga expiración cuando nuestros pulmones se desinflan, como me dice la estudiante de teatro, para sacar la voz hay que tener el cuerpo listo, preparado, con un tono muscular, una respiración determinada. …”
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LUneXt: Simple and Efficient U-shaped Network Design for Medical Image Segmentation with Nonlinear Activation by Guanghong Deng, Bing Yu, Wenlong Jing, Yong Li, Xiaodan Zhao

“…The experimental IoU value of the International Skin Imaging Collaboration (ISIC 2018) data set reached 82.95%, and the Dice value reached 90.50%. The single inference speed reached 842.58[Formula: see text]ms. …”
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A laboratory feasibility study using a computer algorithm for anastomosis segmentation of epicardial ultrasonography images from distal coronary artery bypass anastomoses by Alex Skovsbo Jørgensen, Martin Siemienski Andersen, Lasse Riis Østergaard, Samuel Emil Schmidt, Dorte Nøhr, Jan Jesper Andreasen

“…Results The number of dimensions of anastomotic vessel structures that are relevant for stenosis quantification and the Dice coefficient were 0.888 between the automatic and manual segmentations. …”
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Automatic segmentation of white matter lesions on multi-parametric MRI: convolutional neural network versus vision transformer by Yun-Ting Chen, Yan-Cheng Huang, Hsiu-Ling Chen, Hsin-Chih Lo, Pei-Chin Chen, Chiun-Chieh Yu, Yi-Chin Tu, Tyng-Luh Liu, Wei-Che Lin

“…Four metrics were used for evaluation: Dice similarity coefficient, lesion segmentation, lesion F1-Score, and lesion sensitivity. …”
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Multiscale attention network via topology learning for cerebral vessel segmentation in angiography images by Tao Han, Junchen Xiong, Tingyi Lin, Tao An, Cheng Wang, Jianjun Zhu, Zhongliang Li, Ligong Lu, Yi Zhang, Gao-Jun Teng

“…To maintain the topological connectivity of vessel segmentation, we introduced the clDice loss function to enforce skeleton connectivity of vessel segmentation. …”
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A Hybrid Efficient U-Net Framework for Detection of Anterior Belly of the Digastric Muscle on Ultrasonography by Sule Erdem, Suheda Erdem, Muammer Turkoglu, Abdulkadir Sengur, Nebras M. Sobahi

“…Combo Loss (a combination of Binary Cross-Entropy and Dice Loss) was used to train the model and segmentation metrics such as F1-score, Intersection over Union (IoU) and Dice Co-efficient were used to evaluate performance. …”
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Text similarity detection method based on NLP by Xiaoli DAI, Shifeng LIU, Daqing GONG

“…Current text similarity detection methods that ignore document structure information and lack semantic relevance.To solve these problems, a text-oriented similarity detection method was proposed.First, analytic hierarchy process (AHP) was used to calculate word position weight to extract feature words.Second, the Pearson correlation coefficient was used to measure semantic correlation between words which was the weight of generalized Dice coefficient to calculate similarity.Experimental results show that the proposed method can improve the precision of feature word extraction and the accuracy of similarity calculation results.…”
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Lack of Data and other Problems of Economic Policy Advice in Germany by Justus Haucap

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Making Holes in the Second Symmetric Products of Dendrites and Some Fans by José G. Anaya, David Maya, Fernando Orozco-Zitli

“…Sea X un continuo métrico tal que el segundo producto simétrico de X, F2(X) es unicoherente. Sea A E F2(X), A se dice que hace un hoyo a F2(X), si F2(X) - {A} no es unicoherente. …”
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The Platform Economy: New Competition Rules — Renaissance of Antitrust Control of the Abuse of Market Power by Justus Haucap

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Design and realization of a multisamples rotating high cycle fatigue machine by Domenico Gentile, Massimo Martorelli

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La LOMCE. ¿Una ley más de educación? by José Gimeno Sacristán

“…El Partido Popular, que ha mezclado en el texto las reivindicaciones de los grupos ideológicos que apoyan las políticas conservadoras, muestra importantes contradicciones entre las propuestas que dice que va a desarrollar y las que verdaderamente aplica en los territorios en los que gobierna.…”
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