Multicore embedded sensing system based on lightweight neural network

References

• Shukla SK, Gupta VK, Joshi K, et al. Self-aware execution environment model (SAE2) for the performance improvement of multicore systems. Int J Mod Res. 2022;2(1):17–27.
   Google Scholar
• Incel OD, Bursa SO. On-device deep learning for mobile and wearable sensing applications: a review. IEEE Sens J. 2023;23(6):5501–5512. doi: 10.1109/JSEN.2023.3240854
   Web of Science ®Google Scholar
• Ngo GQ, Najafidehaghani E, Gan Z, et al. In-fibre second-harmonic generation with embedded two-dimensional materials. Nat Photonics. 2022;16(11):769–776. doi: 10.1038/s41566-022-01067-y
   Web of Science ®Google Scholar
• Amin R, Abdulrazak LF, Mohammadd N, et al. GaAs-filled elliptical core-based hexagonal PCF with excellent optical properties for nonlinear optical applications. Ceram Int. 2022;48(4):5617–5625. doi: 10.1016/j.ceramint.2021.11.106
   Web of Science ®Google Scholar
• Sepideh S, Mohsen A, Mohammad S, et al. Energy-budget-aware reliability management in multi-core embedded systems with hybrid energy source. CSI J Comput Sci Eng. 2018;15(2):31–43.
   Google Scholar
• Pablo MA, Diego L, Jose AB, et al. Performance analysis of a millimeter wave MIMO channel estimation method in an embedded multi-core processor. J Supercomputing. 2022;78(12):14756–14767. doi: 10.1007/s11227-022-04479-3
   Web of Science ®Google Scholar
• Mohsen A, Mostafa P, Javad SL, et al. Meeting thermal safe power in fault-tolerant heterogeneous embedded systems. IEEE Embedded Syst Lett. 2019;12(1):29–32. doi: 10.1109/LES.2019.2931882
   Web of Science ®Google Scholar
• Kalyan B, Amlan C. Dynamic scheduling of real-time tasks in heterogeneous multicore systems. IEEE Embedded Syst Lett. 2018;11(1):29–32. doi: 10.1109/LES.2018.2846666
   Web of Science ®Google Scholar
• Bruno SJM, Sandro P. A first look at RISC-V virtualization from an embedded systems perspective. IEEE Trans Comput. 2021;71(9):2177–2190.
   Web of Science ®Google Scholar
• Mohsen A, Sepideh S, Sina YK, et al. Thermal-aware standby-sparing technique on heterogeneous real-time embedded systems. IEEE Trans Emerging Top Comput. 2021;10(4):1883–1897. doi: 10.1109/TETC.2021.3120084
   Web of Science ®Google Scholar
• Amir YK, Mohsen A, Alireza E. ReMap: reliability management of peak-power-aware real-time embedded systems through task replication. IEEE Trans Emerging Top Comput. 2020;10(1):312–323. doi: 10.1109/TETC.2020.3018902
   Web of Science ®Google Scholar
• Ruijie Z, Guan G, Zhi X, et al. A novel intrusion detection method based on lightweight neural network for internet of things. IEEE Int Things J. 2021;9(12):9960–9972. doi: 10.1109/JIOT.2021.3119055
   Web of Science ®Google Scholar
• Moshe K, Asaf S. Efficient cyber attack detection in industrial control systems using lightweight neural networks and PCA. IEEE Trans Dependable Secure Comput. 2021;19(4):2179–2197. doi: 10.1109/TDSC.2021.3050101
   Web of Science ®Google Scholar
• Michal W, Jakub S, Marcin W, et al. Lightweight convolutional neural network model for human face detection in risk situations. IEEE Trans Ind Inform. 2021;18(7):4820–4829. doi: 10.1109/TII.2021.3129629
   Web of Science ®Google Scholar
• Liu X, Di X. TanhExp: a smooth activation function with high convergence speed for lightweight neural networks. IET Computer Vision. 2021;15(2):136–150. doi: 10.1049/cvi2.12020
   Web of Science ®Google Scholar
• Mohammed Y, Yin Y, Shidin B, et al. A lightweight neural network with multiscale feature enhancement for liver CT segmentation. Sci Rep. 2022;12(1):1–12. doi: 10.1038/s41598-022-16828-6
   PubMed Web of Science ®Google Scholar
• Fahed J, Omar A, Dimitrios M, et al. A novel lightweight deep convolutional neural network for early detection of oral cancer. Oral Dis. 2022;28(4):1123–1130. doi: 10.1111/odi.13825
   PubMed Web of Science ®Google Scholar
• Jia S, Lin Z, Xu M, et al. A lightweight convolutional neural network for hyperspectral image classification. IEEE Trans Geosci Remote Sens. 2020;59(5):4150–4163. doi: 10.1109/TGRS.2020.3014313
   Web of Science ®Google Scholar
• Mishra R, Gupta H. Transforming large-size to lightweight deep neural networks for IoT applications. ACM Comput Surv. 2023;55(11):1–35. doi: 10.1145/3570955
   Web of Science ®Google Scholar
• Lin H, Chen H, Yin C, et al. Lightweight residual convolutional neural network for soybean classification combined with electronic nose. IEEE Sens J. 2022;22(12):11463–11473. doi: 10.1109/JSEN.2022.3174251
   Web of Science ®Google Scholar
• Mainak C, Sunita VD, Jitendra I. Corona-Nidaan: lightweight deep convolutional neural network for chest X-Ray based COVID-19 infection detection. Appl Intell. 2021;51(5):3026–3043. doi: 10.1007/s10489-020-01978-9
   PubMed Web of Science ®Google Scholar
• Qiu Z, Zhu X, Liao C, et al. Detection of bird species related to transmission line faults based on lightweight convolutional neural network. IET Gener Transm Distrib. 2022;16(5):869–881. doi: 10.1049/gtd2.12333
   Web of Science ®Google Scholar
• Zhu H, Qiao Y, Gu X, et al. DSPNet: a lightweight dilated convolution neural networks for spectral deconvolution with self-paced learning. IEEE Trans Ind Inform. 2019;16(12):7392–7401. doi: 10.1109/TII.2019.2960837
   Web of Science ®Google Scholar
• Tao Y, Zongyang Z, Jun Z, et al. Low-altitude small-sized object detection using lightweight feature-enhanced convolutional neural network. J Syst Eng Electron. 2021 Aug;32(4):841–853. doi: 10.23919/JSEE.2021.000073
   Web of Science ®Google Scholar
• Iman MRH, Pejman Y. A software control flow checking technique in multi-core processors. Int J Embedded Syst. 2020;13(2):136–147. doi: 10.1504/IJES.2020.108861
   Web of Science ®Google Scholar
• Stauffer J, Zhang Q. s2Cloud: a novel cloud-based precision health system for smart and secure IoT big data harnessing. Discov Internet Things. 2024;4(3). doi: 10.1007/s43926-024-00055-8
   Google Scholar
• Hanbiba S. Water environment monitoring system based on wireless sensor network. Acad J Environ Biol. 2021;2(1):39–47. doi: 10.38007/AJEB.2021.020105
   Google Scholar
• Marcello Z, Simone B, Alessio B, et al. Robust real-time embedded EMG recognition framework using temporal convolutional networks on a multicore IoT processor. IEEE Trans Biomed Circuits Syst. 2019;14(2):244–256. doi: 10.1109/TBCAS.2019.2959160
   PubMed Web of Science ®Google Scholar
• Kumar PJ, Mini MG. Machine learning based workload balancing scheme for minimizing stress migration induced aging in multicore processors. Int J Inf Technol. 2023;15(1):399–410. doi: 10.1007/s41870-022-01105-6
   Google Scholar
• Yi S. EASYR: E nergy-efficient a daptive sy stem R econfiguration for dynamic deadlines in autonomous driving on multicore processors. ACM Trans Embedded Comput Syst. 2023;22(3):1–29. doi: 10.1145/3570503
   Web of Science ®Google Scholar
• Navarro-Torres A, Alastruey-Benedé J, Ibáñez P, et al. BALANCER: bandwidth allocation and cache partitioning for multicore processors. J Supercomput. 2023;79(9):10252–10276. doi: 10.1007/s11227-023-05070-0
   Web of Science ®Google Scholar