Unsupervised learning using pretrained CNN and associative memory bank
Q Liu, S Mukhopadhyay - 2018 International Joint Conference …, 2018 - ieeexplore.ieee.org
Deep Convolutional features extracted from a comprehensive labeled dataset, contain
substantial representations which could be effectively used in a new domain. Despite the …
substantial representations which could be effectively used in a new domain. Despite the …
Multi-modal associative storage and retrieval using Hopfield auto-associative memory network
R Shriwas, P Joshi, VM Ladwani… - … Conference on Artificial …, 2019 - Springer
Recently we presented text storage and retrieval in an auto-associative memory framework
using the Hopfield neural-network. This realized the ideal functionality of Hopfield network …
using the Hopfield neural-network. This realized the ideal functionality of Hopfield network …
M-ary hopfield neural network based associative memory formulation: Limit-cycle based sequence storage and retrieval
VM Ladwani, V Ramasubramanian - … 14–17, 2021, Proceedings, Part IV …, 2021 - Springer
In this paper, we examine Hopfield network composed of multi-state neurons for storing
sequence data as limit cycles of the network. Earlier, we had presented uni-modal data …
sequence data as limit cycles of the network. Earlier, we had presented uni-modal data …
M-ary hopfield neural network for storage and retrieval of variable length sequences: multi-limit cycle approach
VM Ladwani… - 2022 IEEE Symposium …, 2022 - ieeexplore.ieee.org
In this paper, we present M-ary Hopfield neural network based auto-associative memory
formulation for variable length sequences. Each sequence is composed of variable length of …
formulation for variable length sequences. Each sequence is composed of variable length of …
Networks of Coupled VO2 Oscillators for Neuromorphic Computing
E Corti - 2021 - infoscience.epfl.ch
Neuromorphic computing is a wide research field aimed to the realization of brain-inspired
hardware, apt to tackle computation of unstructured data more efficiently than currently done …
hardware, apt to tackle computation of unstructured data more efficiently than currently done …
Neural network control interface of the speaker dependent computer system «Deep Interactive Voice Assistant DIVA» to help people with speech impairments
T Khorosheva, M Novoseltseva, N Geidarov… - Proceedings of the Third …, 2019 - Springer
With the development of modern informational communication systems, voice control
interface and speech recognition systems find application in various fields of activity. One …
interface and speech recognition systems find application in various fields of activity. One …
Quaternionic Recurrent Correlation Neural Networks
ME Valle - 2018 International Joint Conference on Neural …, 2018 - ieeexplore.ieee.org
In this paper, we introduce the class of quaternionic recurrent correlation neural networks
(QRCNNs), which extended the real-valued bipolar recurrent correlation neural networks of …
(QRCNNs), which extended the real-valued bipolar recurrent correlation neural networks of …
[PDF][PDF] CNN Features Off-the-Shelf: Clustering and Finetune-free
Q Liu, S Mukhopadhyay - ltrc.lsu.edu
Deep convolutional features learned from a largescale labeled dataset, contain substantial
representations which could be effectively used in a new domain. Despite the fact that …
representations which could be effectively used in a new domain. Despite the fact that …