AIMC Topic: Neural Networks, Computer

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A multi-layered defense against adversarial attacks in brain tumor classification using ensemble adversarial training and feature squeezing.

Scientific reports
Deep learning, particularly convolutional neural networks (CNNs), has proven valuable for brain tumor classification, aiding diagnostic and therapeutic decisions in medical imaging. Despite their accuracy, these models are vulnerable to adversarial a...

Optimization process of coffee pulp wines combined with the artificial neural network and response surface methodology.

Scientific reports
Coffee pulp wine was made from coffee pulp. The level range of fermentation factors was determined by one-factor experiment. The significance factors affecting fermentation were screened by Plackett-Burman and steepest climbing experiments, which wer...

Water status and plant traits of dry bean assessment using integrated spectral reflectance and RGB image indices with artificial intelligence.

Scientific reports
This study investigated the potential of using remote sensing indices with artificial neural networks (ANNs) to quantify the responses of dry bean plants to water stress. Two field experiments were conducted with three irrigation regimes: 100% (B100)...

Virtual white matter: a novel system for cross-dish neural interaction and modulation.

Journal of neural engineering
. Biological neural networks (BNNs) are characterized by complex interregional connectivity, allowing for seamless communication between different brain regions.models traditionally consist of single-dish neural cultures that cannot recapitulate the ...

Neural Code Translation With LIF Neuron Microcircuits.

Neural computation
Spiking neural networks (SNNs) provide an energy-efficient alternative to traditional artificial neural networks, leveraging diverse neural encoding schemes such as rate, time-to-first-spike (TTFS), and population-based binary codes. Each encoding me...

Dynamics and Bifurcation Structure of a Mean-Field Model of Adaptive Exponential Integrate-and-Fire Networks.

Neural computation
The study of brain activity spans diverse scales and levels of description and requires the development of computational models alongside experimental investigations to explore integrations across scales. The high dimensionality of spiking networks p...

Dynamics of Continuous Attractor Neural Networks With Spike Frequency Adaptation.

Neural computation
Attractor neural networks consider that neural information is stored as stationary states of a dynamical system formed by a large number of interconnected neurons. The attractor property empowers a neural system to encode information robustly, but it...

A fully automatic radiomics pipeline for postoperative facial nerve function prediction of vestibular schwannoma.

Neuroscience
Vestibular schwannoma (VS) is the most prevalent intracranial schwannoma. Surgery is one of the options for the treatment of VS, with the preservation of facial nerve (FN) function being the primary objective. Therefore, postoperative FN function pre...

Modeling heterogeneity, commitment, and memory of bacterial spore germination.

mBio
Spores of bacteria are metabolically dormant, resistant to microbicides, and vectors of food spoilage and diseases and survive for years in their dormant state. Upon exposure to nutrient germinants, spores can rapidly return to life through germinati...

M-GNN: A Graph Neural Network Framework for Lung Cancer Detection Using Metabolomics and Heterogeneous Graph Modeling.

International journal of molecular sciences
Lung cancer remains the leading cause of cancer-related mortality worldwide, with early detection critical for improving survival rates, yet conventional methods like CT scans often yield high false-positive rates. This study introduces M-GNN, a grap...