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Conference code: 162690 Export Date: 14 October 2020 References: Chin, C.D., Linder, V., Sia, S.K., Commercialization of microfluidic point-ofCare diagnostic devices (2012) Lab on A Chip, 12 (12), p. 2118; Clerk Maxwell, J., (1892) A Treatise on Electricity and Magnetism, 2, pp. 68-73. , 3rd ed., Oxford: Clarendon; Quesada-Gonzalez, D., Merkoci, A., NanomaterialBased devices for point-ofCare diagnostic applications (2018) Chemical Society Reviews; Williams, L.W., Interpretation of diagnostic tests (2000) Indian Journal of Pediatrics, 67 (1), pp. 49-53; Hassan, U., (2013) Microfluidic Sensor for White Blood Cell Counting and Flow Metering; Temiz, Y., Lab-on-AChip devices: How to close and plug the lab Microelectronic Engineering, 132 (2015), pp. 156-175; Cha, C.H., Erythrocyte sedimentation rate measurements by test 1 better reflect inflammation than do those by the westergren method in Patients with Malignancy, Autoimmune Disease, or Infection Am J Clin Pathol, 131 (2), pp. 189-194. , http://www.oxfordbiosystems.com/Portals/0/PDF/Biomedomics/COVID19Flyer.pdf, BioMedomics COVID-19 IgM/IgG Rapid test,2009 Feb; Jiang, R., Crookes, D., Luo, N., Davidson, M.W., LiveCell tracking using SIFT features in DIC microscopic videos (2010) IEEE Trans. Biomed Eng., 57, pp. 2219-2228; Fernyhough, E.N., (2016) Automated Segmentation of Structures Essential to Cell Movement, , Diss.University of Leeds; Xia, T., Jiang, R., Fu, Y.Q., Jin, N., Automated blood cell detection and counting via deep learning for microfluidic point-ofcare medical devices 2019 3rd International Conference on Artificial Intelligence Applications and Technologies AIAAT 2019, , 1-3 August 2019, Beijing, China; Storey, G., Jiang, R., Bouridane, A., Role for 2D image generated 3D face models in the rehabilitation of facial palsy (2017) IET Healthcare Technology Letters; Storey, G., Bouridane, A., Jiang, R., Integrated deep model for face detection and landmark localisation from 'in the wild' images IEEE Access, , in press; Storey, G., Jiang, R., Bouridane, A., Role for 2D image generated 3D face models in the rehabilitation of facial palsy (2017) IET Healthcare Technology Letters; Jiang, Z., Chazot, P.L., Celebi, M.E., Crookes, D., Jiang, R., Social behavioral phenotyping of drosophila with a 2d-3d hybrid cnn framework (2019) IEEE Access, pp. 67972-67982; Jiang, R., Crookes, D., Shallow unorganized neural networks using smart neuron model for visual perception (2019) IEEE Access, pp. 152701-152714; Girshick, R., Rich feature hierarchies for accurate object detection and semantic segmentation (2014) Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition; Girshick, R., Fast rCnn (2015) Proceedings of the IEEE International Conference on Computer Vision; Ren, S., Faster rCnn: Towards realTime object detection with region proposal networks (2015) Advances in Neural Information Processing Systems; Kaiming, H., Mask rCnn (2017) Proceedings of the IEEE International Conference on Computer Vision; Redmon, J., You only look once: Unified, realTime object detection (2016) Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition; Redmon, J., Farhadi, A., (2018) YOLOv3: An Incremental Improvement, , http://github.com/ultralytics/YOLOv3; Redmon, J., Farhadi, A., YOLO9000: Better, faster, stronger (2017) Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition; BCCD Dataset, , http://github.com/Shenggan/BCCDDatset; Mitra, A., Leukoerythroblastic reaction in a patient with covid-19 infection American Journal of Hematology, , Mar 25 2020; Jiang, R., Almaadeed, S., Bouridane, A., Crookes, D., Celebi, M.E., Face recognition in the scrambled domain via salience-Aware ensembles of many kernels (2016) IEEE Trans. Information Forensics and Security, 11 (8), pp. 1807-1817; Jiang, R., Bouridane, A., Crookes, D., Celebi, M., Wei, H.L., PrivacyProtected facial biometric verification via fuzzy forest learning (2016) IEEE Trans. Fuzzy Systems, 24 (4), pp. 779-790; Jiang, R., Sadka, A.H., Crookes, D., Multimodal biometric human recognition for perceptual human-computer interaction (2010) IEEE Trans. Systems, Man, & Cybernetics Part C, 40 (5), p. 676; Jiang, R., Ho, A., Cheheb, I., Almaadeed, N., Almaadeed, S., Bouridane, A., Emotion recognition from scrambled facial images via many graph embedding (2017) Pattern Recognition, 67, pp. 245-251; Soares, E., Angelov, P., Novelty Detection and Learning with Extremely Weak Supervision, , http://arxiv.org/pdf/1911.00616.pdf