AIMC Topic: Memory

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Non-Local Temporal Difference Network for Temporal Action Detection.

Sensors (Basel, Switzerland) Nov 1, 2022
As an important part of video understanding, temporal action detection (TAD) has wide application scenarios. It aims to simultaneously predict the boundary position and class label of every action instance in an untrimmed video. Most of the existing ...
Neural Networks, Computer Memory
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The Portiloop: A deep learning-based open science tool for closed-loop brain stimulation.

PloS one Aug 22, 2022
Closed-loop brain stimulation refers to capturing neurophysiological measures such as electroencephalography (EEG), quickly identifying neural events of interest, and producing auditory, magnetic or electrical stimulation so as to interact with brain...
Memory Electric Stimulation Electroencephalography Brain Deep Learning Deep Brain Stimulation
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Waveform detection by deep learning reveals multi-area spindles that are selectively modulated by memory load.

eLife Jun 29, 2022
Sleep is generally considered to be a state of large-scale synchrony across thalamus and neocortex; however, recent work has challenged this idea by reporting isolated sleep rhythms such as slow oscillations and spindles. What is the spatial scale of...
Animals Deep Learning Memory Electrocorticography Electroencephalography Sleep
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A Flexible Artificial Sensory Nerve Enabled by Nanoparticle-Assembled Synaptic Devices for Neuromorphic Tactile Recognition.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Jun 9, 2022
Tactile perception enabled by somatosensory system in human is essential for dexterous tool usage, communication, and interaction. Imparting tactile recognition functions to advanced robots and interactive systems can potentially improve their cognit...
Humans Robotics Memory Nanoparticles Electronics Touch
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Reservoir Memory Machines as Neural Computers.

IEEE transactions on neural networks and learning systems Jun 1, 2022
Differentiable neural computers (DNCs) extend artificial neural networks with an explicit memory without interference, thus enabling the model to perform classic computation tasks, such as graph traversal. However, such models are difficult to train,...
Neural Networks, Computer Computers Language Memory
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Memory Recall: A Simple Neural Network Training Framework Against Catastrophic Forgetting.

IEEE transactions on neural networks and learning systems May 2, 2022
It is widely acknowledged that biological intelligence is capable of learning continually without forgetting previously learned skills. Unfortunately, it has been widely observed that many artificial intelligence techniques, especially (deep) neural ...
Artificial Intelligence Brain Neural Networks, Computer Learning Memory
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A deep neural network model for multi-view human activity recognition.

PloS one Jan 7, 2022
Multiple cameras are used to resolve occlusion problem that often occur in single-view human activity recognition. Based on the success of learning representation with deep neural networks (DNNs), recent works have proposed DNNs models to estimate hu...
Recognition, Psychology Learning Attention Memory Human Activities Humans Neural Networks, Computer
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Measuring context dependency in birdsong using artificial neural networks.

PLoS computational biology Dec 28, 2021
Context dependency is a key feature in sequential structures of human language, which requires reference between words far apart in the produced sequence. Assessing how long the past context has an effect on the current status provides crucial inform...
Memory Vocalization, Animal Finches Computational Biology Cluster Analysis Neural Networks, Computer Animals Algorithms Male
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Retrospective memory integration accompanies reconfiguration of neural cell assemblies.

Hippocampus Dec 21, 2021
Memory is a dynamic process that is based on and can be altered by experiences. Integrating memories of multiple experiences (memory integration) is the basis of flexible and complex decision-making. However, the mechanism of memory integration in ne...
Neural Networks, Computer Neuronal Plasticity Artificial Intelligence Memory Retrospective Studies
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Ambulatory seizure forecasting with a wrist-worn device using long-short term memory deep learning.

Scientific reports Nov 9, 2021
The ability to forecast seizures minutes to hours in advance of an event has been verified using invasive EEG devices, but has not been previously demonstrated using noninvasive wearable devices over long durations in an ambulatory setting. In this s...
Electroencephalography Adult Male Seizures Female Wrist Wearable Electronic Devices Middle Aged Humans Memory Young Adult Deep Learning Forecasting Cohort Studies
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