Unsupervised online learning of temporal information in spiking neural network using TFT-type NOR flash memory devices.
Sign Up to like & getrecommendations! Published in 2019 at "Nanotechnology"
DOI: 10.1088/1361-6528/ab34da
Abstract: Brain-inspired analogue neuromorphic systems based on synaptic array have attracted large attention due to low-power computing. Spike-timing-dependent plasticity (STDP) algorithm is considered as one of the appropriate neuro-inspired techniques to be applied for on-chip learning.… read more here.
Keywords: learning temporal; unsupervised online; tft type; network ... See more keywords
Learning Temporal Dynamics for Video Super-Resolution: A Deep Learning Approach
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2018.2820807
Abstract: Video super-resolution (SR) aims at estimating a high-resolution video sequence from a low-resolution (LR) one. Given that the deep learning has been successfully applied to the task of single image SR, which demonstrates the strong… read more here.
Keywords: learning temporal; resolution; video super; super resolution ... See more keywords
Multidimensional Hebbian Learning With Temporal Coding in Neocognitron Visual Recognition
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Systems, Man, and Cybernetics: Systems"
DOI: 10.1109/tsmc.2016.2599200
Abstract: Previous work on Fuskushima’s neocognitron neural network model has mostly focused on binary character recognition, but grayscale images are preferable to binary images in real applications. Image classes of grayscale objects can be formed with… read more here.
Keywords: learning temporal; coding neocognitron; temporal coding; multidimensional hebbian ... See more keywords
Unsupervised Learning of Temporal Abstractions With Slot-Based Transformers
Sign Up to like & getrecommendations! Published in 2022 at "Neural Computation"
DOI: 10.48550/arxiv.2203.13573
Abstract: Abstract The discovery of reusable subroutines simplifies decision making and planning in complex reinforcement learning problems. Previous approaches propose to learn such temporal abstractions in an unsupervised fashion through observing state-action trajectories gathered from executing… read more here.
Keywords: learning temporal; based transformers; abstractions slot; temporal abstractions ... See more keywords