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BrainCog: A Spiking Neural Network based Brain-inspired Cognitive Intelligence Engine for Brain-inspired AI and Brain Simulation [article]

Yi Zeng, Dongcheng Zhao, Feifei Zhao, Guobin Shen, Yiting Dong, Enmeng Lu, Qian Zhang, Yinqian Sun, Qian Liang, Yuxuan Zhao, Zhuoya Zhao, Hongjian Fang (+7 others)
2022 arXiv   pre-print
Spiking neural networks (SNNs) have attracted extensive attentions in Brain-inspired Artificial Intelligence and computational neuroscience.  ...  spiking neural network based AI, and to simulate the cognitive brains at multiple scales.  ...  Some details are introduced as follows: 1) Visual Emotion Recognition: For emotion recognition, inspired by the ventral visual pathway, we construct a deep convolutional spiking neural network with LIF  ... 
arXiv:2207.08533v1 fatcat:pb2ah43qlra7zmvhr4no27ovcu

Progress and Challenges of Neuroscience and Brain-inspired Artificial Intelligence

Lidong Wang, Cheryl Ann Alexander
2020 Neuroscience International  
graph, brain networks, the connectome, brain reconstruction, imaging technologies used for the brain, chips and devices inspired by the human brain, brain-computer interface or brain-machine interfaces  ...  , cyborg, neuro-robotics, and quantum robotics.  ...  Acknowledgement The authors would like to thank Technology and Healthcare Solutions, Mississippi, USA and the Institute for IT innovation and Smart Health, Mississippi, USA for support.  ... 
doi:10.3844/amjnsp.2020.1.9 fatcat:apbgz22m6ffwzehijvq662pvwe

Progress and Challenges of Neuroscience and Brain-inspired Artificial Intelligence

Lidong Wang, Cheryl Ann Alexander
2019 Neuroscience International  
graph, brain networks, the connectome, brain reconstruction, imaging technologies used for the brain, chips and devices inspired by the human brain, brain-computer interface or brain-machine interfaces  ...  , cyborg, neuro-robotics, and quantum robotics.  ...  Acknowledgement The authors would like to thank Technology and Healthcare Solutions, Mississippi, USA and the Institute for IT innovation and Smart Health, Mississippi, USA for support.  ... 
doi:10.3844/amjnsp.2019.13.21 fatcat:dtoa5moa2bhwdbiaxe6belwlf4

Analysis and Modelling of Strong-AI to Engineer BIONIC Brain for Humanoid Robotics Application

Md. Sadique Shaikh
2013 American Journal of Embedded Systems and Applications  
Networks, Neural Schema's for strong -AI,Genetic algorithms, Advanced logic engineering for pattern /object recognit translation (Natural Language Processing), readings, facial expression, love and desire  ...  Networks, Neural algorithms, Advanced logic engineering for pattern /object recognition and Natural Language Processing), readings, facial expression, love and desire and human like response smart programs  ... 
doi:10.11648/j.ajesa.20130102.11 fatcat:a5dw7yzzunflre7tbsvdhmy3h4

Neurocognitive Informatics Manifesto [article]

Włodzisław Duch
2021 arXiv   pre-print
In this position paper examples of neurocognitive inspirations and promising directions in this area are given.  ...  Neurocognitive informatics is a new, emerging field that should help to improve the matching of artificial and natural systems, and inspire better computational algorithms to solve problems that are still  ...  The use of wave-like representation in terms of basis functions to describe neural states makes this formalism similar to that used in quantum mechanics, although no real quantum effects are implied here  ... 
arXiv:2101.03609v1 fatcat:newlygw52vfytmfxtvtlzrohju

Conversational Transfer Learning for Emotion Recognition [article]

Devamanyu Hazarika, Soujanya Poria, Roger Zimmermann, Rada Mihalcea
2020 arXiv   pre-print
Given the large amount of available conversational data, we investigate whether generative conversational models can be leveraged to transfer affective knowledge for detecting emotions in context.  ...  Overall, we infer that knowledge acquired from dialogue generators can indeed help recognize emotions in conversations.  ...  We also gratefully acknowledge the support of NVIDIA Corporation with the donation of a Titan Xp GPU used for this research.  ... 
arXiv:1910.04980v3 fatcat:wz2a4txienhlba5r2q76cswtjq

Discovering Emotion and Reasoning its Flip in Multi-Party Conversations using Masked Memory Network and Transformer [article]

Shivani Kumar, Anubhav Shrimal, Md Shad Akhtar, Tanmoy Chakraborty
2021 arXiv   pre-print
To this end, we consider MELD, a benchmark emotion recognition dataset in multi-party conversations for the task of ERC, and augment it with new ground-truth labels for EFR.  ...  We propose a masked memory network to address the former and a Transformer-based network for the latter task.  ...  They used quantum-inspired interactive networks, which leverages the mathematical formalism of quantum theory and the LSTM network, to learn such interaction dynamics. Wang et al.  ... 
arXiv:2103.12360v3 fatcat:5zpzvcu3mbdflbqz2mnmx4r5ze

Front Matter

2020 2020 International Joint Conference on Neural Networks (IJCNN)  
Beijing, China, China 5:45PM A Multi-Population FA for Automatic Facial Emotion Recognition [#21155] Kamlesh Mistry, Baqar Rizvi, Chris Rook, Sadaf Iqbal, Li Zhang and Colin Paul Joy Dept. of computer  ...  filter in a Spiking Convolutional Neural Network: a preliminary study [#21556] Shriya Gupta and Basabdatta Bhattacharya BITS Pilani Goa Campus, India P1314 Application of Spiking Neural Networks for  ... 
doi:10.1109/ijcnn48605.2020.9207579 fatcat:hptkppolhbfn7nz3yangesetpi

A Novel Approach for Classification of Speech Emotions Based on Deep and Acoustic Features

Mehmet Bilal Er
2020 IEEE Access  
In [33] , a hybrid deep neural network model has been proposed for heterogeneous acoustic features that reduce classification performance in speech emotion recognition problem.  ...  In [30] , to effectively improve speech emotion recognition performance, a novel speech emotion recognition technique is presented that depends on Deep Neural Network (DNN), decision tree and SVM.  ...  In [58] , presents a speech emotion recognition system using the recurrent neural network (RNN) model.  ... 
doi:10.1109/access.2020.3043201 fatcat:khpnyeyqvjej5mg7scdexbplfu

Neural Networks for Emotion Classification [article]

Yafei Sun
2011 arXiv   pre-print
Finally, we perform several experiments and show that our neural network approach can be successfully used for emotion recognition.  ...  One of these skills is the ability to understand the emotional state of the person. This thesis describes a neural network-based approach for emotion classification.  ...  We can transform this unsupervised neural network into a supervised LVQ (Learning Vector Quantum) neural network, which is another clustering technique.  ... 
arXiv:1105.6014v1 fatcat:ck3x6tl3vfgxvlg5ad5rawrmuq

2014 Index IEEE Transactions on Neural Networks and Learning Systems Vol. 25

2014 IEEE Transactions on Neural Networks and Learning Systems  
., +, TNNLS Jul. 2014 1346-1358 Shift registers ERNN: A Biologically Inspired Feedforward Neural Network to Discriminate Emotion From EEG Signal.  ...  ., +, TNNLS May 2014 908-919 Feature extraction ERNN: A Biologically Inspired Feedforward Neural Network to Discrimi- nate Emotion From EEG Signal.  ...  The Field of Values of a Matrix and Neural Networks. Georgiou, G.M., TNNLS Sep. 2014  ... 
doi:10.1109/tnnls.2015.2396731 fatcat:ztnfcozrejhhfdwg7t2f5xlype

Accelerating Decision-Making in Transport Emergency with Artificial Intelligence

Alexander Raikov
2020 Advances in Science, Technology and Engineering Systems  
emotions of participants.  ...  The paper addresses speeding up meetings in a networked environment during rescue works in a transport emergency.  ...  Acknowledgment Supported by the Russian Foundation for Basic Research, grant No 18-29-03086 "Methods for identifying the needs of economic sectors in digital platforms and end-to-end technologies based  ... 
doi:10.25046/aj050662 fatcat:iir66vfz6beb5jn6j3y4ykqz4u

The Why, What and How of Artificial General Intelligence Chip Development [article]

Alex James
2021 arXiv   pre-print
The AI chips increasingly focus on implementing neural computing at low power and cost. The intelligent sensing, automation, and edge computing applications have been the market drivers for AI chips.  ...  Finally, the design consideration required for building an AGI chip is listed along with the methods for testing and validating it.  ...  The possibility for quantum chips to run several operations in parallel, inspire the design for quantum neural network.  ... 
arXiv:2012.06338v2 fatcat:chwmoukdnnccllj3i6to7kb6ha

Quantum mechanics in the brain

Christof Koch, Klaus Hepp
2006 Nature  
The role of quantum mechanics for the photons received by the eye and for the molecules of life is not controversial.  ...  A small minority, however, maintains that quantum mechanics is important for understanding higher brain functions, e.g. for the generation of voluntary movements (free will), for high-level perception  ...  The neural correlate for 'holding in place a template' is a well-studied function of recurrent networks in cortex.  ... 
doi:10.1038/440611a pmid:16572152 fatcat:czgo7ggs35ferce2bkxix327y4

ICCE 2020 TOC

2020 2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)  
- 314 65 146 A Relative Comparison of Training Algorithms in Artificial Neural Network Saurav Kumar, Rishabh Kumar Mishra, Anuran Mitra, Soumita Biswas, Sayantani De and Raja Karmakar 315-  ...  Sreemoyee Bose, Supriyo Das, Arijit Dey, Jyotirmoy Das and Syamasree Biswas Raha 269- 274 57 129 Feature Extraction and Classification of Phonocardiograms using Convolutional Neural Networks  ... 
doi:10.1109/icce50343.2020.9290745 fatcat:eln5gj5hr5chddqhecxlm7lpda
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