3.8 Proceedings Paper

SpikeMS: Deep Spiking Neural Network for Motion Segmentation

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Proceedings Paper Automation & Control Systems

0-MMS: Zero-Shot Multi-Motion Segmentation With A Monocular Event Camera

Chethan M. Parameshwara et al.

Summary: This study presents a novel approach for monocular multi-motion segmentation, combining feature tracking and motion compensation to split and merge scenes into multiple motions. By using motion propagation and cluster keyslices, the method is further accelerated. The method has been successfully evaluated on challenging real-world and synthetic scenarios, outperforming the state-of-the-art detection rate.

2021 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2021) (2021)

Article Computer Science, Artificial Intelligence

Unsupervised Learning of a Hierarchical Spiking Neural Network for Optical Flow Estimation: From Events to Global Motion Perception

Federico Paredes-Valles et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2020)

Proceedings Paper Computer Science, Artificial Intelligence

Event-based attention and tracking on neuromorphic hardware

Alpha Renner et al.

2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW 2019) (2019)

Proceedings Paper Computer Science, Artificial Intelligence

EV-IMO: Motion Segmentation Dataset and Learning Pipeline for Event Cameras

Anton Mitrokhin et al.

2019 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) (2019)

Proceedings Paper Computer Science, Artificial Intelligence

Event-Based Motion Segmentation by Motion Compensation

Timo Stoffregen et al.

2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2019) (2019)

Article Multidisciplinary Sciences

A Spiking Neural Network Model of Depth from Defocus for Event- based Neuromorphic Vision

Germain Haessig et al.

SCIENTIFIC REPORTS (2019)

Article Computer Science, Hardware & Architecture

Loihi: A Neuromorphic Manycore Processor with On-Chip Learning

Mike Davies et al.

IEEE MICRO (2018)

Article Computer Science, Artificial Intelligence

SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks

Friedemann Zenke et al.

NEURAL COMPUTATION (2018)

Article Computer Science, Artificial Intelligence

STDP-based spiking deep convolutional neural networks for object recognition

Saeed Reza Kheradpisheh et al.

NEURAL NETWORKS (2018)

Review Neurosciences

Deep Learning With Spiking Neurons: Opportunities and Challenges

Michael Pfeiffer et al.

FRONTIERS IN NEUROSCIENCE (2018)

Proceedings Paper Computer Science, Artificial Intelligence

A Low Power, Fully Event-Based Gesture Recognition System

Arnon Amir et al.

30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017) (2017)

Article Neurosciences

Training Deep Spiking Neural Networks Using Backpropagation

Jun Haeng Lee et al.

FRONTIERS IN NEUROSCIENCE (2016)

Article Computer Science, Hardware & Architecture

True North: Design and Tool Flow of a 65 mW 1 Million Neuron Programmable Neurosynaptic Chip

Filipp Akopyan et al.

IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS (2015)

Article Computer Science, Artificial Intelligence

HFirst: A Temporal Approach to Object Recognition

Garrick Orchard et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2015)

Article Neurosciences

Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccades

Garrick Orchard et al.

Frontiers in Neuroscience (2015)

Article Engineering, Electrical & Electronic

A QVGA 143 dB Dynamic Range Frame-Free PWM Image Sensor With Lossless Pixel-Level Video Compression and Time-Domain CDS

Christoph Posch et al.

IEEE JOURNAL OF SOLID-STATE CIRCUITS (2011)

Article Engineering, Electrical & Electronic

A 128x128 120 dB 15 μs latency asynchronous temporal contrast vision sensor

Patrick Lichtsteiner et al.

IEEE JOURNAL OF SOLID-STATE CIRCUITS (2008)

Article Computer Science, Artificial Intelligence

A novel spike distance

MCW van Rossum

NEURAL COMPUTATION (2001)