AIMC Topic: Neural Networks, Computer

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Highly robust reconstruction framework for three-dimensional optical imaging based on physical model constrained neural networks.

Physics in medicine and biology
. The reconstruction of three-dimensional optical imaging that can quantitatively acquire the target distribution from surface measurements is a serious ill-posed problem. Traditional regularization-based reconstruction can solve such ill-posed probl...

Small object detection algorithm incorporating swin transformer for tea buds.

PloS one
Accurate identification of small tea buds is a key technology for tea harvesting robots, which directly affects tea quality and yield. However, due to the complexity of the tea plantation environment and the diversity of tea buds, accurate identifica...

Can neural networks benefit from objectives that encourage iterative convergent computations? A case study of ResNets and object classification.

PloS one
Recent work has suggested that feedforward residual neural networks (ResNets) approximate iterative recurrent computations. Iterative computations are useful in many domains, so they might provide good solutions for neural networks to learn. However,...

Physics-Informed Deep Learning for Muscle Force Prediction With Unlabeled sEMG Signals.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Computational biomechanical analysis plays a pivotal role in understanding and improving human movements and physical functions. Although physics-based modeling methods can interpret the dynamic interaction between the neural drive to muscle dynamics...

DeepPLM_mCNN: An approach for enhancing ion channel and ion transporter recognition by multi-window CNN based on features from pre-trained language models.

Computational biology and chemistry
Accurate classification of membrane proteins like ion channels and transporters is critical for elucidating cellular processes and drug development. We present DeepPLM_mCNN, a novel framework combining Pretrained Language Models (PLMs) and multi-wind...

PSE-Net: Channel pruning for Convolutional Neural Networks with parallel-subnets estimator.

Neural networks : the official journal of the International Neural Network Society
Channel Pruning is one of the most widespread techniques used to compress deep neural networks while maintaining their performances. Currently, a typical pruning algorithm leverages neural architecture search to directly find networks with a configur...

Toxicity prediction and classification of Gunqile-7 with small sample based on transfer learning method.

Computers in biology and medicine
Drug-induced diseases are the most important component of iatrogenic disease. It is the duty of doctors to provide a reasonable and safe dose of medication. Gunqile-7 is a Mongolian medicine with analgesic and anti-inflammatory effects. As a foreign ...

Deep Learning-Based construction of a Drug-Like compound database and its application in virtual screening of HsDHODH inhibitors.

Methods (San Diego, Calif.)
The process of virtual screening relies heavily on the databases, but it is disadvantageous to conduct virtual screening based on commercial databases with patent-protected compounds, high compound toxicity and side effects. Therefore, this paper uti...

eDeeplepsy: An artificial neural framework to reveal different brain states in children with epileptic spasms.

Epilepsy & behavior : E&B
OBJECTIVE: Despite advances, analysis and interpretation of EEG still essentially rely on visual inspection by a super-specialized physician. Considering the vast amount of data that composes the EEG, much of the detail inevitably escapes ordinary hu...

Solar desalination system for fresh water production performance estimation in net-zero energy consumption building: A comparative study on various machine learning models.

Water science and technology : a journal of the International Association on Water Pollution Research
This study employs diverse machine learning models, including classic artificial neural network (ANN), hybrid ANN models, and the imperialist competitive algorithm and emotional artificial neural network (EANN), to predict crucial parameters such as ...