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Automatic counting and positioning of slaughter pigs within the pen using a convolutional neural network and video images

• Authors : Jensen, Dan Børge; Pedersen, Lene Juul

Subjects: Convolutional neural network; Growing pigs; Machine vision

• Source: Jensen , D B & Pedersen , L J 2021 , ' Automatic counting and positioning of slaughter pigs within the pen using a convolutional neural

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Automatic counting and positioning of slaughter pigs within the pen using a convolutional neural network and video images

• Authors : Jensen, Dan Børge; Pedersen, Lene Juul

Subjects: Convolutional neural network; Growing pigs; Machine vision

• Source: Jensen , D B & Pedersen , L J 2021 , ' Automatic counting and positioning of slaughter pigs within the pen using a convolutional neural

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Mapping Cretaceous faults using a convolutional neural network - A field example from the Danish North Sea

• Authors : Lorentzen, Mads C. L.; Bredesen, Kenneth; Smit, Florian W. H.

Subjects: Machine learning; fault detection; cap-rock integrity

• Source: Lorentzen , M C L , Bredesen , K , Smit , F W H , Hansen , T H , Nielsen , L & Mosegaard , K 2022 , ' Mapping Cretaceous faults using a convolutional

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Bundle geodesic convolutional neural network for diffusion-weighted imaging segmentation

• Authors : Liu, Renfei; Lauze, Francois; Erleben, Kenny

Subjects: G-convolutional neural networks; group convolution; geometric deep learning

• Source: Liu , R , Lauze , F , Erleben , K , Berg , R W & Darkner , S 2022 , ' Bundle geodesic convolutional neural

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A convolutional neural network for total tumor segmentation in [ 64 Cu]Cu-DOTATATE PET/CT of patients with neuroendocrine neoplasms

• Authors : Carlsen, Esben Andreas; Lindholm, Kristian; Hindsholm, Amalie

Subjects: Artificial intelligence; Neuroendocrine neoplasms; Prognostication

• Source: Carlsen , E A , Lindholm , K , Hindsholm , A , Gæde , M , Ladefoged , C N , Loft , M , Johnbeck , C B , Langer , S W , Oturai , P , Knigge , U , Kjaer , A & Andersen , F L 2022 , ' A

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A convolutional neural network for total tumor segmentation in [ 64 Cu]Cu-DOTATATE PET/CT of patients with neuroendocrine neoplasms

• Authors : Carlsen, Esben Andreas; Lindholm, Kristian; Hindsholm, Amalie

Subjects: Artificial intelligence; Neuroendocrine neoplasms; Prognostication

• Source: Carlsen , E A , Lindholm , K , Hindsholm , A , Gæde , M , Ladefoged , C N , Loft , M , Johnbeck , C B , Langer , S W , Oturai , P , Knigge , U , Kjaer , A & Andersen , F L 2022 , ' A

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Bundle geodesic convolutional neural network for diffusion-weighted imaging segmentation

• Authors : Liu, Renfei; Lauze, Francois; Erleben, Kenny

Subjects: G-convolutional neural networks; group convolution; geometric deep learning

• Source: Liu , R , Lauze , F , Erleben , K , Berg , R W & Darkner , S 2022 , ' Bundle geodesic convolutional neural

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Cloth and Skin Deformation with a Triangle Mesh Based Convolutional Neural Network

• Authors : Chentanez, Nuttapong; Macklin, Miles; Müller, Matthias

• Source: Chentanez , N , Macklin , M , Müller , M , Jeschke , S & Kim , T 2020 , ' Cloth and Skin Deformation with a Triangle Mesh Based Convolutional

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Comparison of strategies for automatic video-based detection of piling behaviour in laying hens

• Authors : Jensen, Dan Børge; Toscano, Michael; van der Heide, Esther

Subjects: Automatic monitoring; Convolutional neural network; Fully-connected neural network

• Source: Jensen , D B , Toscano , M , van der Heide , E , Grønvig , M & Hakansson , F 2025 , ' Comparison of strategies for automatic video-based detection of piling behaviour in laying hens ' , Smart

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A generic deep convolutional neural network framework for prediction of receptor–ligand interactions - NetPhosPan:application to kinase phosphorylation prediction

• Authors : Fenoy, Emilio; Izarzugaza, Jose M.G.; Jurtz, Vanessa

• Source: Fenoy , E , Izarzugaza , J M G , Jurtz , V , Brunak , S & Nielsen , M 2019 , ' A generic deep convolutional neural

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