AIMC Topic: Neural Networks, Computer

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Body Weight Estimation for Pigs Based on 3D Hybrid Filter and Convolutional Neural Network.

Sensors (Basel, Switzerland)
The measurement of pig weight holds significant importance for producers as it plays a crucial role in managing pig growth, health, and marketing, thereby facilitating informed decisions regarding scientific feeding practices. On one hand, the conven...

Understanding and interpreting CNN's decision in optical coherence tomography-based AMD detection.

European journal of ophthalmology
INTRODUCTION: Automated assessment of age-related macular degeneration (AMD) using optical coherence tomography (OCT) has gained significant research attention in recent years. Though a list of convolutional neural network (CNN)-based methods has bee...

Advances in AI-Driven Retention Prediction for Different Chromatographic Techniques: Unraveling the Complexity.

Critical reviews in analytical chemistry
Retention prediction through Artificial intelligence (AI)-based techniques has gained exponential growth due to their abilities to process complex sets of data and ease the crucial task of identification and separation of compounds in most employed c...

Coupling synthetic and real-world data for a deep learning-based segmentation process of 4D flow MRI.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Phase contrast magnetic resonance imaging (4D flow MRI) is an imaging technique able to provide blood velocity in vivo and morphological information. This capability has been used to study mainly the hemodynamics of large ve...

A varying-parameter fixed-time gradient-based dynamic network for convex optimization.

Neural networks : the official journal of the International Neural Network Society
We focus on the fixed-time convergence and robustness of gradient-based dynamic networks for solving convex optimization. Most of the existing gradient-based dynamic networks with fixed-time convergence have limited ability to resist interferences of...

A fusion framework of deep learning and machine learning for predicting sgRNA cleavage efficiency.

Computers in biology and medicine
CRISPR/Cas9 system is a powerful tool for genome editing. Numerous studies have shown that sgRNAs can strongly affect the efficiency of editing. However, it is still not clear what rules should be followed for designing sgRNA with high cleavage effic...

Neuromorphic Sentiment Analysis Using Spiking Neural Networks.

Sensors (Basel, Switzerland)
Over the past decade, the artificial neural networks domain has seen a considerable embracement of deep neural networks among many applications. However, deep neural networks are typically computationally complex and consume high power, hindering the...

RNA contact prediction by data efficient deep learning.

Communications biology
On the path to full understanding of the structure-function relationship or even design of RNA, structure prediction would offer an intriguing complement to experimental efforts. Any deep learning on RNA structure, however, is hampered by the sparsit...

MLP-Like Model With Convolution Complex Transformation for Auxiliary Diagnosis Through Medical Images.

IEEE journal of biomedical and health informatics
Medical images such as facial and tongue images have been widely used for intelligence-assisted diagnosis, which can be regarded as the multi-label classification task for disease location (DL) and disease nature (DN) of biomedical images. Compared w...

Design and Evaluation of Deep Learning Models for Continuous Acute Pain Detection Based on Phasic Electrodermal Activity.

IEEE journal of biomedical and health informatics
The current method for assessing pain in clinical practice is subjective and relies on self-reported scales. An objective and accurate method of pain assessment is needed for physicians to prescribe the proper medication dosage, which could reduce ad...