1,199 research outputs found
CarSNN: An Efficient Spiking Neural Network for Event-Based Autonomous Cars on the Loihi Neuromorphic Research Processor
Autonomous Driving (AD) related features provide new forms of mobility that
are also beneficial for other kind of intelligent and autonomous systems like
robots, smart transportation, and smart industries. For these applications, the
decisions need to be made fast and in real-time. Moreover, in the quest for
electric mobility, this task must follow low power policy, without affecting
much the autonomy of the mean of transport or the robot. These two challenges
can be tackled using the emerging Spiking Neural Networks (SNNs). When deployed
on a specialized neuromorphic hardware, SNNs can achieve high performance with
low latency and low power consumption. In this paper, we use an SNN connected
to an event-based camera for facing one of the key problems for AD, i.e., the
classification between cars and other objects. To consume less power than
traditional frame-based cameras, we use a Dynamic Vision Sensor (DVS). The
experiments are made following an offline supervised learning rule, followed by
mapping the learnt SNN model on the Intel Loihi Neuromorphic Research Chip. Our
best experiment achieves an accuracy on offline implementation of 86%, that
drops to 83% when it is ported onto the Loihi Chip. The Neuromorphic Hardware
implementation has maximum 0.72 ms of latency for every sample, and consumes
only 310 mW. To the best of our knowledge, this work is the first
implementation of an event-based car classifier on a Neuromorphic Chip.Comment: Accepted for publication at IJCNN 202
Trends and oscillations in the Indian summer monsoon rainfall over the last two millennia
Observations show that summer rainfall over large parts of South Asia has declined over the past five to six decades. It remains unclear, however, whether this trend is due to natural variability or increased anthropogenic aerosol loading over South Asia. Here we use stable oxygen isotopes in speleothems from northern India to reconstruct variations in Indian monsoon rainfall over the last two millennia. We find that within the long-term context of our record, the current drying trend is not outside the envelope of monsoon’s oscillatory variability, albeit at the lower edge of this variance. Furthermore, the magnitude of multi-decadal oscillatory variability in monsoon rainfall inferred from our proxy record is comparable to model estimates of anthropogenic-forced trends of mean monsoon rainfall in the 21st century under various emission scenarios. Our results suggest that anthropogenic forced changes in monsoon rainfall will remain difficult to detect against a backdrop of large natural variability
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