Results 31 to 40 of about 2,305,737 (285)

LSUnetMix: Fuse channel feature information with long–short term memory

open access: yesIET Computer Vision, 2023
Medical image segmentation based on deep learning is becoming popular. To improve the segmentation accuracy of medical images such as cells and vessels, we propose the LSUnetMix model, which can effectively enhance the ability to extract channel ...
Chao Yuan, Yanbo Wang, Yunxuan Xiao
doaj   +1 more source

Short-Term Plasticity and Long-Term Potentiation in Magnetic Tunnel Junctions: Towards Volatile Synapses

open access: yes, 2016
Synaptic memory is considered to be the main element responsible for learning and cognition in humans. Although traditionally non-volatile long-term plasticity changes have been implemented in nanoelectronic synapses for neuromorphic applications, recent
Roy, Kaushik, Sengupta, Abhronil
core   +1 more source

Tree Memory Networks for Modelling Long-term Temporal Dependencies

open access: yes, 2018
In the domain of sequence modelling, Recurrent Neural Networks (RNN) have been capable of achieving impressive results in a variety of application areas including visual question answering, part-of-speech tagging and machine translation.
Denman, Simon   +4 more
core   +1 more source

Short-term memory and long-term memory are still different. [PDF]

open access: yes, 2017
A commonly expressed view is that short-term memory (STM) is nothing more than activated long-term memory. If true, this would overturn a central tenet of cognitive psychology-the idea that there are functionally and neurobiologically distinct short- and
Norris, Dennis
core   +1 more source

Criterion‐Related Validity of the Neuropsychological Quick Assessment for Screening Cognitive, Motor, and Behavioral Impairments in Patients With Pediatric Brain Tumors: An Observational Pilot Study

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background Neuropsychological complications may impair the qualitative prognosis of patients with pediatric brain tumors. However, multifaceted evaluations cannot be conducted in all patients because they are time consuming and burdensome for patients.
Ami Tabata   +9 more
wiley   +1 more source

Survival of the Fittest: Increased Stimulus Competition During Encoding Results in Fewer but More Robust Memory Traces [PDF]

open access: yes, 2019
Forgetting can be accounted for by time-indexed decay as well as competition-based interference processes. Although conventionally seen as competing theories of forgetting processes, Altmann and colleagues argued for a functional interaction between ...
Baumann, Oliver   +2 more
core   +1 more source

Rapid Response to Trametinib Combined With Chemotherapy for Infant BRAF‐Fused Chiasmatic Glioma

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Infants, less than 1 year, with chiasmatic gliomas (ICG) present a major therapeutic challenge due to large tumor size, decreased vision, rapid progression, and poor response to vincristine/carboplatin chemotherapy. The majority have a BRAF fusion, which may respond to downstream MEK inhibitors but response time is slow. There are no safety or
Helen Toledano   +7 more
wiley   +1 more source

Aircraft Gearbox Fault Diagnosis System: An Approach based on Deep Learning Techniques

open access: yesJournal of Intelligent Systems, 2020
Gearbox is one of the vital components in aircraft engines. If any small damage to gearbox, it can cause the breakdown of aircraft engine. Thus it is significant to study fault diagnosis in gearbox system.
Mallikarjuna P B   +3 more
doaj   +1 more source

Antimicrobial peptides modulate long-term memory. [PDF]

open access: yesPLoS Genetics, 2018
Antimicrobial peptides act as a host defense mechanism and regulate the commensal microbiome. To obtain a comprehensive view of genes contributing to long-term memory we performed mRNA sequencing from single Drosophila heads following behavioral training
Raquel Barajas-Azpeleta   +7 more
doaj   +1 more source

Memory Networks [PDF]

open access: yes, 2015
We describe a new class of learning models called memory networks. Memory networks reason with inference components combined with a long-term memory component; they learn how to use these jointly. The long-term memory can be read and written to, with the
Bordes, Antoine   +2 more
core  

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