Recent Publications in Smart Sensors

Conference Papers/Presentations

  1. (Invited) M. Lee, She, B. Chakraborty, S. Dash, B. A. Mudassar, and S. Mukhopadhyay, “Reliable Edge Intelligence in Unreliable Environment” Design, Automation and Test in Europe (DATE), 2021
  2. M. Mukherjee, B. A. Mudassar, M. Lee and S. Mukhopadhyay, “Algorithm-Circuit Cross-layer Control for Digital Pixel Image Sensors,” IEEE Sensors 2020. Best Student Paper Award, Third Place.
  3. B. A. Mudassar, P. Saha and S. Mukhopadhyay, “Uncertainty Characterization in Active Sensor Systems with DNN-based Feedback Control,” IEEE Sensors 2020.
  4. M. Lee, M. Mukherjee, P. Saha, M. F. Amir, T. Na, and S. Mukhopadhyay, “Effect of Process Variations in Digital Pixel Circuits on the Accuracy of DNN based Smart Sensor,” IEEE International Conference on Artificial Intelligence Circuits and Systems, March 2020.
  5. (Invited) A. Mudassar, P. Saha, Y. Long, M. F. Amir, E. Gebhardt, T. Na, J. H. Ko, M. Wolf and S. Mukhopadhyay, “A Camera With Brain – Embedding Machine Learning In 3d Image Sensor,” Design Automation and Test in Europe(DATE), March 2019.
  6. J. H. Ko, T. Na, M. F. Amir, and S. Mukhopadhyay, “Edge-Host Partitioning of Deep Neural Networks with Feature Space Encoding for Resource-Constrained Internet-of-Things Platforms,” IEEEInternational Conference on Advanced Video and Signal-based Surveillance(AVSS), 2018.
  7. P. Saha, B. A Mudassar, and S. Mukhopadhyay, “Adaptive Control of Camera Modality with Deep Neural Network-Based Feedback for Efficient Object Tracking,” IEEEInternational Conference on Advanced Video and Signal-based Surveillance (AVSS), 2018.
  8. M. F. Amir, J. H. Ko, and S. Mukhopadhyay,” An Image Sensor SOC with Energy Harvesting Mixed-Vth Pixel Generating 5.8uW/mm2 Power Density and 0.77 Frames/second Self-Powered Frame Rate ,”IEEE SOI-3D-Subthreshold Microelectronics Technology Unified Conference (S3S), 2018.
  9. M. F. Amir and S. Mukhopadhyay, “3D Stacked High Throughput Pixel Parallel Image Sensor with Integrated ReRAM Based Neural Accelerator,”  IEEE SOI-3D-Subthreshold Microelectronics Technology Unified Conference (S3S), 2018.
  10. B. A. Mudassar, J. H. Ko, and S. Mukhopadhyay, “Edge-Cloud Collaborative Processing for Intelligent Internet of Things: A Case Study on Smart Surveillance,” Design Automation Conference (DAC), 2018.
  11. B. A. Mudassar, J. H. Ko, and S. Mukhopadhyay, “An Unsupervised Anomalous Event Detection Framework With Class Aware Source Separation,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018.
  12. T. Na, J. H. Ko, and S. Mukhopadhyay, “Noise-Robust And Resolution-Invariant Image Classification With Pixel-Level Regularization,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018.
  13. (Invited) S. Mukhopadhyay, M. Wolf, M. F. Amir, E. Gebahrdt, J. H. Ko, J. H. Kung, and B. A. Musassar, “The CAMEL Approach to Stacked Sensor Smart Cameras, Design, Automation, and Test in Europe (DATE), 2018.
  14. (Invited) J. H. Ko, Y. Long, M. F. Amir, D. Kim, J. Kung, T. Na, A. Trivedi, and S. Mukhopadhyay, “Energy-Efficient Neural Image Processing for Internet-of-Things Edge Devices,” IEEE International Midwest Symposium on Circuits and Systems (MWSCAS 2017), Aug. 2017.
  15. J. H. Ko, D. Kim, T. Na, J. Kung, and S. Mukhopadhyay, “Adaptive Weight Compression for Memory-Efficient Neural Networks,” Design, Automation, and Test in Europe (DATE 2017).
  16. M. F. Amir, D. Kim, J. Kung, D. Lie, S. Yalamanchili, and S. Mukhopadhyay, NeuroSensor: A 3D Image Sensor with Integrated Neural Accelerator, IEEE SOI-3D-Subthreshold Microelectronics Technology Unified Conference (S3S), 2016. Best Student Paper Award
  17. K. Z. Ahmed, M. F. Amir, J. H. Ko, and S. Mukhopadhyay, “Reconfigurable 96×128 Active Pixel Sensor with 2.1mW/mm2 Power Generation and Regulated Multidomain Power Delivery for Self-Powered Imaging,” IEEE European Solid State Circuit Conference (ESSCIRC), 2016.
  18. J. H. Ko, T. Na, and S. Mukhopadhyay, “An Energy-Efficient Wireless Video Sensor Node with a Region-of-Interest Based Multi-Parameter Rate Controller for Moving Object Surveillance,” 2016 IEEE Advanced Video and Signal-based Surveillance (AVSS 2016), Aug. 2016.
  19. J. H. Ko and S. Mukhopadhyay, “An Energy-Aware Approach to Noise-Robust Moving Object Detection for Low-Power Wireless Image Sensor Platforms,” IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED), 2016 (Best Paper Award).
  20. J. H. Kung, D. Kim, and S. Mukhopadhyay, “Dynamic Approximation with Feedback Control for Energy-Efficient Recurrent Neural Network Hardware,” IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED), 2016.
  21. J. H. Ko, K. Ahmed, M. F. Amir, and S. Mukhoapdhyay, “A Self-powered Wireless Video Sensor Node for Moving Object Surveillance,” GOMACTECH 2016
  22. A. Trivedi, R. Pandey, H. Liu, S. Datta, and S. Mukhopadhyay, “Gate/Source Overlapped Heterojunction Tunnel FET for non-Boolean Associative Processing with Plasticity,” IEEE International Electron Device Meeting (IEDM), Dec. 2015.
  23. J. H. Kung, D. Kim, and S. Mukhopadhyay, “A Power-Aware Digital Feedforward Neural Network Platform with Backpropagation Driven Approximate Synapses,” IEEE/ACM International Symposium on Low Power Electronic Design (ISLPED), July 2015.
  24. D. Lie, K. Chae, and S. Mukhopadhyay, “On the Impact of 3D Integration on High-Throughput Sensor Information Processing: A Case Study with Image Sensing,” NANOARCH, July 2013.

Journal Articles 

  1. M. Lee, B. Mudassar, and S. Mukhopadhyay, “Adaptive Camera Platform using Deep Learning based Early Warning of Task Failures”, accepted for publication in IEEE Sensors Journal.
  2. M. Lee, M. Mukherjee, E. Lee, P. Saha, M. Amir, T. Na, and S. Mukhopadhyay, “Cross-Layer Noise Analysis in Smart Digital Pixel Sensors with Integrated Deep Neural Network,” IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS), vol. 10, no. 4, Dec. 2020, pp. 444-457.
  3. A. Shylendra, P. Shukla, S. Mukhopadhyay, S. Bhunia, and A. R. Trivedi, “Low Power Unsupervised Anomaly Detection by Non-Parametric Modeling of Sensor Statistics,” IEEE Transactions on VLSI Systems (TVLSI), vol. 28, no. 8, August 2020, pp. 1833-1843.
  4. P. Saha and S. Mukhopadhyay, “Multispectral Information Fusion with Reinforcement Learning for Object Tracking in IoT Edge Devices,” IEEE Sensors Journal, vol. 20, no. 8, April 2020, pp. 4333 – 4344.
  5. B. Mudassar, P. Saha, Y. Long, M. F. Amir, E. Gebhardt, T. Na, J. H. Ko, M. Wolf, and S. Mukhopadhyay, “CAMEL: An Adaptive Camera with Embedded Machine Learning Based Sensor Parameter Control,” IEEE Journal of Emerging Technologies in Circuits and Systems (JETCAS), vo. 9 , no. 3, Sept. 2019, pp. 498-508.
  6. S. MukhopadhyayY. LongB. Mudassar, C. Nair,B. H. Deprospo, H. M. Torun, M. Kathaperumal, V. Smet, D. Kim, S. Yalamanchili, and M. Swaminathan, “Heterogenous Integration for Artificial Intelligence: Challenges and Opportunities,” IBM Journal of Research and Development (IBM J. R&D), vol. 63 , no. 6 , Nov.-Dec. 2019, pp. 4.1-4.23.
  7. J. H. Ko, T. Na, and S. Mukhopadhyay, “An Energy-Quality Scalable Wireless Image Sensor Node for Object-Based Video Surveillance,”  IEEE Journal of Emerging and Selected Topics in Circuits and Systems (IEEE JETCAS).
  8. M. F. Amir, J. H. Ko, T. Na, D. Kim, and S. Mukhopadhyay, “3D Stacked Image Sensor with Deep Neural Network Computation,” IEEE Sensors Journal, vol. 18, no. 10,  May, 2018, pp. 4187 – 4199.
  9. J. H. Ko, D. Kim, T. Na, and S. Mukhopadhyay, “Design and Analysis of a Neural Network Inference Engine based on Adaptive Weight Compression,” accepted for publication in IEEE Transactions on Computer Aided Design (TCAD).
  10. J. H. Ko, K. Z. Ahmed, M. F. Amir, T. Na, and S. Mukhopadhyay, “A Single-Chip Image Sensor Node with Energy Harvesting from CMOS Pixel Array” J. H. Ko, M. F. Amir, K. Z. Ahmed, T. Na and S. Mukhopadhyay, “ IEEE Transactions on Circuits and Systems I: Regular Papers (TCAS), vol. 64, no. 9, Sept. 2017, pp. 2295-2307.
  11. D. Kim, J. H. Kung, and S. Mukhopadhyay, “A Power-Aware Digital Multilayer Perceptron Accelerator with On-Chip Training based on Approximate Computing,” IEEE Transactions on Emerging Topics in Computing (IEEE TETC), vol. 5, no. 2, April-June 2017, pp. 164-178.
  12. D. Lie, A. Trivedi, and S. Mukhopadhyay, “Impact of Heterogeneous Technology Integration on the Power, Performance, and Quality of a 3D Image Sensor,” IEEE Transactions on Multi-Scale Computing Systems (TMSCS), Vol. 2, No. 1, Jan-March, 2016, pp. 61-67.
  13. M. F. Amir, A. Trivedi, and S. Mukhopadhyay, “Exploration of Si/Ge Tunnel FET Bit Cells for Ultra-low Power Embedded Memory,” IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS), vol. 6, no. 2, June 2016, pp. 185-197.
  14. J. H. Ko, B. Muhammad, and S. Mukhopadhyay, “An Energy-Efficient Wireless Video Sensor Node for Moving Object Surveillance,” IEEE Transactions on Multi-Scale Computing Systems (TMSCS), Vol. 1, No. 1, Sept. 2015, pp. 7-18.
  15. D. Lie, K. Chae, and S. Mukhopadhyay, “Analysis of the Performance, Power, and Noise Characteristics of a CMOS Image Sensor with 3D Integrated Image Compression Unit,” IEEE Transactions on Components, Packaging, and Manufacturing Technologies (TCPMT), vol. 4, no.2, Feb. 2014, pp.198-208.