AIMC Topic: Neural Networks, Computer

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Sparse connectivity enables efficient information processing in cortex-like artificial neural networks.

Frontiers in neural circuits
Neurons in cortical networks are very sparsely connected; even neurons whose axons and dendrites overlap are highly unlikely to form a synaptic connection. What is the relevance of such sparse connectivity for a network's function? Surprisingly, it h...

Prediction of acute toxicity of organic contaminants to fish: Model development and a novel approach to identify reactive substructures.

Journal of hazardous materials
In this study, count-based Morgan fingerprints (CMF) were employed to represent the fundamental chemical structures of contaminants, and a neural network model (R² = 0.76) was developed to predict acute fish toxicity (AFT) of organic compounds. Model...

Dual-pathway EEG model with channel attention for virtual reality motion sickness detection.

Journal of neuroscience methods
BACKGROUND: Motion sickness has been a key factor affecting user experience in Virtual Reality (VR) and limiting the development of the VR industry. Accurate detection of Virtual Reality Motion Sickness (VRMS) is a prerequisite for solving the proble...

UniSAL: Unified Semi-supervised Active Learning for histopathological image classification.

Medical image analysis
Histopathological image classification using deep learning is crucial for accurate and efficient cancer diagnosis. However, annotating a large amount of histopathological images for training is costly and time-consuming, leading to a scarcity of avai...

DCAlexNet: Deep coupled AlexNet for micro facial expression recognition based on double face images.

Computers in biology and medicine
Facial Micro-Expression Recognition (FER) presents challenges due to individual variations in emotional intensity and the complexity of feature extraction. While apex frames offer valuable emotional information, their precise role in FER remains uncl...

Dynamic Bonding for In-Situ Welding of Multilayer Elastomers Enables High-Performance Wearable Electronics for Machine Learning-Assisted Active Rehabilitation.

Advanced materials (Deerfield Beach, Fla.)
Patients with hand dysfunction require joint rehabilitation for functional restoration, and wearable electronics can provide physical signals to assess and guide the process. However, most wearable electronics are susceptible to failure under large d...

Interpretable deep learning for deconvolutional analysis of neural signals.

Neuron
The widespread adoption of deep learning to model neural activity often relies on "black-box" approaches that lack an interpretable connection between neural activity and network parameters. Here, we propose using algorithm unrolling, a method for in...

Accelerated Missense Mutation Identification in Intrinsically Disordered Proteins Using Deep Learning.

Biomacromolecules
We use a combination of Brownian dynamics (BD) simulation results and deep learning (DL) strategies for the rapid identification of large structural changes caused by missense mutations in intrinsically disordered proteins (IDPs). We used ∼6500 IDP s...

Multidependency Graph Convolutional Networks and Contrastive Learning for Drug Repositioning.

Journal of chemical information and modeling
The goal of drug repositioning is to expedite the drug development process by finding novel therapeutic applications for approved drugs. Using multifeature learning, different computational drug repositioning techniques have recently been introduced ...

Real-Time Acoustic Scene Recognition for Elderly Daily Routines Using Edge-Based Deep Learning.

Sensors (Basel, Switzerland)
The demand for intelligent monitoring systems tailored to elderly living environments is rapidly increasing worldwide with population aging. Traditional acoustic scene monitoring systems that rely on cloud computing are limited by data transmission d...