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Norm Loss: An efficient yet effective regularization method for deep neural networks.

, , , , and . ICPR, page 8812-8818. IEEE, (2020)

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PREPRINT: Comparison of deep learning and hand crafted features for mining simulation data., , , , , and . CoRR, (2021)Preprint: Norm Loss: An efficient yet effective regularization method for deep neural networks., , , , and . CoRR, (2021)Comparison of deep learning and hand crafted features for mining simulation data., , , , , and . ICPR, page 3396-3403. IEEE, (2020)Norm Loss: An efficient yet effective regularization method for deep neural networks., , , , and . ICPR, page 8812-8818. IEEE, (2020)Applying the Participatory Design Workshop Method to Explore how Socially Assistive Robots Could Assist Stroke Survivors., , , and . HRI (Companion), page 203-205. ACM, (2020)Future forums: A methodology for exploring, gamifying, and raising security awareness of code-citizens., , , and . Int. J. Hum. Comput. Stud., (2023)Deep Learning for Instance Retrieval: A Survey., , , , , , , and . IEEE Trans. Pattern Anal. Mach. Intell., 45 (6): 7270-7292 (June 2023)Rhythmic Haptic Cueing for Gait Rehabilitation of Neautological Conditions., , and . BCS HCI, BCS, (2016)Learning Fluid Flows., , , , , and . IJCNN, page 1-8. IEEE, (2018)Assessing the Accuracy of an Algorithm for the Estimation of Spatial Gait Parameters Using Inertial Measurement Units: Application to Healthy Subject and Hemiparetic Stroke Survivor., , , , , and . MOCO, page 5:1-5:7. ACM, (2017)