Advancing fault prediction: A comparative study between LSTM and spiking neural networks
Predicting system faults is critical to improving productivity, reducing costs, and enforcing
safety in industrial processes. Yet, traditional methodologies frequently falter due to the …
safety in industrial processes. Yet, traditional methodologies frequently falter due to the …
An artificial neural slam framework for event-based vision
The SLAM problem for autonomous robots can be greatly improved by using event-based
cameras. Compared to others, event-based cameras consume very low power while …
cameras. Compared to others, event-based cameras consume very low power while …
An intelligent path planning of welding robot based on multisensor interaction
CC Tran, CY Lin - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
Industrial robots are evolving rapidly in the manufacturing industry. There are two main
techniques for programming the robots such as online and offline programming. However …
techniques for programming the robots such as online and offline programming. However …
NET-TEN: a silicon neuromorphic network for low-latency detection of seizures in local field potentials
Objective. Therapeutic intervention in neurological disorders still relies heavily on
pharmacological solutions, while the treatment of patients with drug resistance remains an …
pharmacological solutions, while the treatment of patients with drug resistance remains an …
Highly efficient neuromorphic learning system of spiking neural network with multi-compartment leaky integrate-and-fire neurons
A spiking neural network (SNN) is considered a high-performance learning system that
matches the digital circuits and presents higher efficiency due to the architecture and …
matches the digital circuits and presents higher efficiency due to the architecture and …
Mss-depthnet: Depth prediction with multi-step spiking neural network
Event cameras are considered to have great potential for computer vision and robotics
applications because of their high temporal resolution and low power consumption …
applications because of their high temporal resolution and low power consumption …
Performance comparison of dvs data spatial downscaling methods using spiking neural networks
A Gruel, J Martinet… - Proceedings of the …, 2023 - openaccess.thecvf.com
Abstract Dynamic Vision Sensors (DVS) are an unconventional type of camera that
produces sparse and asynchronous event data, which has recently led to a strong increase …
produces sparse and asynchronous event data, which has recently led to a strong increase …
Enhancing SNN-based spatio-temporal learning: A benchmark dataset and Cross-Modality Attention model
Abstract Spiking Neural Networks (SNNs), renowned for their low power consumption, brain-
inspired architecture, and spatio-temporal representation capabilities, have garnered …
inspired architecture, and spatio-temporal representation capabilities, have garnered …
Direct signal encoding with analog resonate-and-fire neurons
HM Lehmann, J Hille, C Grassmann, V Issakov - IEEE Access, 2023 - ieeexplore.ieee.org
Sensors are an essential element in a wide range of applications. As the number of sensors
increases, so does the amount of data collected with them. This raises the challenge of …
increases, so does the amount of data collected with them. This raises the challenge of …
Spiking Neural Networks for Fast-Moving Object Detection on Neuromorphic Hardware Devices Using an Event-Based Camera
Table tennis is a fast-paced and exhilarating sport that demands agility, precision, and fast
reflexes. In recent years, robotic table tennis has become a popular research challenge for …
reflexes. In recent years, robotic table tennis has become a popular research challenge for …