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Wearable affect and stress recognition: A review., , , and . CoRR, (2018)PPG-based Heart Rate Estimation with Time-Frequency Spectra: A Deep Learning Approach., , , and . UbiComp/ISWC Adjunct, page 1283-1292. ACM, (2018)CNN-based sensor fusion techniques for multimodal human activity recognition., , , , , and . ISWC, page 158-165. ACM, (2017)Wearable-Based Affect Recognition - A Review., , , and . Sensors, 19 (19): 4079 (2019)Deep PPG: Large-Scale Heart Rate Estimation with Convolutional Neural Networks., , , and . Sensors, 19 (14): 3079 (2019)Introducing WESAD, a Multimodal Dataset for Wearable Stress and Affect Detection., , , , and . ICMI, page 400-408. ACM, (2018)Prediction of electrocardiography features points using seismocardiography data: a machine learning approach., , , , , , and . UbiComp, page 96-99. ACM, (2018)Multi-target affect detection in the wild: an exploratory study., , , , and . UbiComp, page 211-219. ACM, (2019)Gaussian Process Density Counting from Weak Supervision., , , , , and . ECCV (1), volume 9905 of Lecture Notes in Computer Science, page 365-380. Springer, (2016)Labelling Affective States "in the Wild": Practical Guidelines and Lessons Learned., , , and . UbiComp/ISWC Adjunct, page 654-659. ACM, (2018)