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Open Neuromorphic
Open Neuromorphic (ONM) provides two things: (i) A curated list of software frameworks to make it easier for everyone to find the tool. (ii)A platform for your code. If you wish to create a new repository or migrate your existing code to ONM, please get in touch with us. You will be made a member of this organisation immediately….
Guillermo Gallego and others
A collection of resources related to event-based vision, a type of computer vision that processes visual data as a stream of events, rather than traditional frame-based methods. The repository contains links to relevant papers, datasets, and tutorials to help further research and development in this field….
IBM Research
This dataset was used to build the real-time, gesture recognition system described in the CVPR 2017 paper titled “A Low Power, Fully Event-Based Gesture Recognition System.” The data was recorded using a DVS128. The dataset contains 11 hand gestures from 29 subjects under 3 illumination conditions and is released under a Creative Commons Attribution 4.0 license….
Garrick Orchard and others
A spiking version of the original frame-based Caltech101 dataset. The N-Caltech101 dataset was captured by mounting the ATIS sensor on a motorized pan-tilt unit and having the sensor move while it views Caltech101 examples on an LCD monitor as shown in the video below….
Applied Brain Research
This dataset contains power benchmarking code for running a simple two-layer, 256-neuron-per-layer neural network keyword spotter on both neuromorphic and conventional hardware devices….
Shikhar Gupta
This is a Python implementation of a hardware efficient spiking neural network. It includes modified learning and prediction rules which could be realised on hardware in an energy efficient way. The aim is to develop a network which could be used for on-chip learning and prediction….
Neuromatch Academy
We have curated a curriculum that spans most areas of computational neuroscience (a hard task in an increasingly big field!). We will expose you to both theoretical modeling and more data-driven analyses. This section will overview the curriculum….
Alexandros Pitilakis and others
Beam Propagation Method (BPM) for planar photonic integrated circuits (PIC), implemented in MATLAB with finite-differences….
Tiffany Hwu and others
A complete neuromorphic solution to outdoor navigation and path planning. The proposed solution is based on a spiking neural network that mimics the biological nervous system of insects. The solution is tested in a real-world scenario and demonstrates promising results in terms of accuracy and efficiency….
Carlos Rios and others
A photonic platform that can combine integrated optics with collocated data storage and processing to enable all-photonic, in-memory computations. By employing nonvolatile photonic elements based on a special phase-change material, it can achieve direct scalar and matrix-vector multiplication, featuring a novel single-shot Write/Erase and a drift-free process….
iniLabs
An asynchronous event-based silicon cochlea. The board takes stereo audio inputs; the custom chip asynchronously outputs a stream of address-events representing activity in different frequency ranges. As such it is a silicon model of the cochlea, the auditory inner ear….
Institute for Cognitive Systems, Technical University of Munich
A multimodal tactile-sensing module for humanoid robots. By integrating various sensing technologies, this module enables robots to perceive complex tactile information such as force, pressure, temperature, and texture….
Tasbolat Taunyazov
NeuTouch is a neuromorphic fingertip tactile sensor that scales well with the number of taxels. The proposed Visual-Tactile Spiking Neural Network (VT-SNN) also enables fast perception when coupled with event sensors. The proposed visual-tactile system (using the NeuTouch and Prophesee event camera) is evaluated on two robot tasks: container classification and rotational slip detection….
Debarun Sengupta and others
An approach entailing carbon nanofiber–polydimethylsiloxane composite-based piezoresistive sensors, coupled with spiking neural networks, to mimic skin-like sensing….
Sony and Prophesee
Metavision Sensing and Software offer all the resources to work with event-driven cameras. The sensational IMX636ES is the new event-driven sensor created by a collaboration between Sony and PROPHESEE. The Metavision software offers 95 algorithms, 67 code samples and 11 ready-to-use applications to be used with this new generation of cameras….
Inivation AG
A high-resolution event-based sensors that only output event streams. Compared to the DAVIS series, it can provide (640 x 480) resolution, but is not able to output greyscale images….
Inivation AG
A dynamic and active pixel vision sensor (DAVIS), which addresses the lack of greyscale output of the DVXplorer series by utilising asynchronous DVS events and synchronous global shutter frames concurrently. The active pixel sensor (APS) circuits and the DVS circuits within a pixel share a single photodiode….
Bodo Rueckauer and others
An open-source software platform for compiling and running deep spiking neural networks (SNNs) on the Intel Loihi neuromorphic hardware platform. The paper introduces the NxTF API, which provides a simple interface for defining and training SNNs using common deep learning frameworks, and the NxTF compiler, which translates trained SNN models into executable code for the Loihi chip….
Nanyang Technological University
A user-friendly package providing easy access to advanced biosignal processing routines. Researchers and clinicians without extensive knowledge of programming or biomedical signal processing can analyze physiological data with only two lines of code….
Telluride Engineering Workshop Participants – Institute of Neuromorphic Engineering
A set of tools that allow users to decode brain signals into the signals that generated them. It can determine whether the signals come from visual or auditory stimuli, and whether they are measured with EEG, MEG, ECoG or any other neural response for decoding. This toolbox is provided as Matlab and Python code, along with documentation and some sample EEG and MEG data….
Guillaume Bellec and others
A tensorflow 1.12 library and a tutorial to train a Long short-term memory Spiking Neural Network. The proposed model uses a method of network rewiring to keep a sparse connectivity during training, which is called DEEP R….
Peter Blouw and others
A power benchmarking code for running a simple two-layer, 256 neuron per layer neural network keyword spotter on both neuromorphic and conventional hardware devices. On conventional devices a Tensorflow version of the keyword spotter is used, while on neuromorphic devices (Loihi), an architecturally identical Nengo version is used….
Perception and Robotics Group, UMD
A project that explores the use of event cameras in dynamic obstacle dodging tasks. Unlike traditional cameras. The project uses deep learning techniques to train a neural network to predict the trajectory of moving obstacles and generate control signals for a drone to avoid collisions in real-time….