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Pooling spike neural network for fast rendering in global illumination.

, , and . Neural Comput. Appl., 32 (2): 427-446 (2020)

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Pooling Spike Neural Network for Acceleration of Global Illumination Rendering., , and . IWANN (1), volume 10305 of Lecture Notes in Computer Science, page 199-211. Springer, (2017)Partitioning of Transportation Networks by Efficient Evolutionary Clustering and Density Peaks., , , and . Algorithms, 15 (3): 76 (2022)On the Use of Deep Active Semi-Supervised Learning for Fast Rendering in Global Illumination., , and . J. Imaging, 6 (9): 91 (2020)Perception of noise in global illumination based on inductive learning., , , and . IJCNN, page 5021-5028. IEEE, (2016)Control of a robot manipulator and pendubot system using artificial neural networks., , and . Robotica, 23 (6): 781-784 (2005)Image noise detection in global illumination methods based on FRVM., , , and . Neurocomputing, (2015)Graph Convolution Networks for Unsupervised Learning., , , and . SADASC, volume 1677 of Communications in Computer and Information Science, page 24-33. Springer, (2022)Image Noise Detection in Global Illumination Methods Based on Fast Relevance Vector Machine., , , and . IWANN (2), volume 7903 of Lecture Notes in Computer Science, page 467-479. Springer, (2013)A global methodology for modeling and simulating medical systems., , , , and . Healthcom, page 466-471. IEEE, (2014)Pooling spike neural network for fast rendering in global illumination., , and . Neural Comput. Appl., 32 (2): 427-446 (2020)