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Arindam Basu
Nanyang Technological University
130Publications
17H-index
1,012Citations
Publications 130
Newest
In this paper, we present EBBIOT-a novel paradigm for object tracking using stationary neuromorphic vision sensors in low-power sensor nodes for the Internet of Video Things (IoVT). Different from fully event based tracking or fully frame based approaches, we propose a mixed approach where we create event-based binary images (EBBI) that can use memory efficient noise filtering algorithms. We exploit the motion triggering aspect of neuromorphic sensors to generate region proposals based on event ...
#1Shoeb Shaikh (NTU: Nanyang Technological University)
#2Rosa Q. SoH-Index: 7
Last.Arindam Basu (NTU: Nanyang Technological University)H-Index: 17
view all 5 authors...
Fully implantable wireless intra-cortical Brain Machine Interfaces (iBMI) is one of the most promising next frontiers in the nascent field of neurotechnology. However, scaling the number of channels in such systems by another 10X is difficult due to power and bandwidth requirements of the wireless transmitter. One promising solution for that is to include more processing, up to the decoder, in the implant so that transmission data rate is reduced drastically. Earlier work on neuromorphic decoder...
#1Yi Chen (NTU: Nanyang Technological University)H-Index: 4
#2Zheng Wang (CAS: Chinese Academy of Sciences)H-Index: 4
Last.Arindam Basu (NTU: Nanyang Technological University)H-Index: 17
view all 4 authors...
Energy-efficient machine-learning and physical unclonable function (PUF) has drawn significant attention for Internet-of-Things (IoT) application in wake-up detection for bandwidth/computation reduction and privacy protection at sensor node or autonomous device. A machine-learning and PUF engine for IoT applications is presented in this paper with a current mirror cross-bar (CMCB) being a shared core circuit for both functions, leading to reduction in overhead area by 48.5×. A novel dimension ex...
May 1, 2019 in ISCAS (International Symposium on Circuits and Systems)
#1Yi Chen (NTU: Nanyang Technological University)H-Index: 4
#2Zheng Wang (CAS: Chinese Academy of Sciences)H-Index: 4
Last.Arindam Basu (NTU: Nanyang Technological University)H-Index: 17
view all 4 authors...
Energy-efficient machine-learning and physical unclonable function (PUF) becomes popular in Internet-of-Things (IoT) applications for saliency detection and privacy protection at sensor node. A machine-learning and PUF engine for IoT applications is presented in this work with a current mirror cross-bar (CMCB) array being a shared core, reducing silicon area. A novel dimension expansion technique is proposed to increase weight matrix dimension beyond the physically implemented array with small h...
May 1, 2019 in ISCAS (International Symposium on Circuits and Systems)
#1Jyotibdha Acharya (NTU: Nanyang Technological University)H-Index: 1
#2Vandana Padala (NTU: Nanyang Technological University)H-Index: 1
Last.Arindam Basu (NTU: Nanyang Technological University)H-Index: 17
view all 3 authors...
This paper presents a three layer spiking neural network based region proposal network operating on data generated by neuromorphic vision sensors. The proposed architecture consists of refractory, convolution and clustering layers designed with bio-realistic leaky integrate and fire (LIF) neurons and synapses. The proposed algorithm is tested on traffic scene recordings from a DAVIS sensor setup. The performance of the region proposal network has been compared with event based mean shift algorit...
May 1, 2019 in ISCAS (International Symposium on Circuits and Systems)
#1Pradeep Kumar Gopalakrishnan (NTU: Nanyang Technological University)H-Index: 1
#2Bapi Kar (NTU: Nanyang Technological University)
Last.Arindam Basu (NTU: Nanyang Technological University)H-Index: 17
view all 5 authors...
This live demo aims to show the performance of a two-layer neural network applied to predictive maintenance. The first layer encodes features based on prior knowledge, while the second layer is trained online to detect anomalies. The system is implemented on an FPGA, acquiring real-time data from sensors attached to a motor. Faults can be triggered artificially in real-time to demonstrate anomaly detection.
#1Shoeb Shaikh (NTU: Nanyang Technological University)
#2Rosa Q. So (Agency for Science, Technology and Research)H-Index: 7
Last.Arindam Basu (NTU: Nanyang Technological University)H-Index: 17
view all 5 authors...
This paper presents for the first time a real-time closed loop neuromorphic decoder chip-driven intra-cortical brain machine interface (iBMI) in a non-human primate (NHP) based experimental setup. Decoded results show trial success rates and mean times to target comparable to those obtained by hand-controlled joystick. Neural control trial success rates of approximately 96% of those obtained by hand-controlled joystick have been demonstrated. Also, neural control has shown mean target reach spee...
Jan 21, 2019 in ASP-DAC (Asia and South Pacific Design Automation Conference)
#1Sumon Kumar Bose (NTU: Nanyang Technological University)
#2Bapi Kar (NTU: Nanyang Technological University)
Last.Arindam Basu (NTU: Nanyang Technological University)H-Index: 17
view all 5 authors...
In Industry 4.0, predictive maintenance (PdM) is one of the most important applications pertaining to the Internet of Things (IoT). Machine learning is used to predict the possible failure of a machine before the actual event occurs. However, main challenges in PdM are: (a) lack of enough data from failing machines, and (b) paucity of power and bandwidth to transmit sensor data to cloud throughout the lifetime of the machine. Alternatively, edge computing approaches reduce data transmission and ...
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