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   Articles with "trained models" as a keyword



Generally trained models to predict drug solubility in N-methyl-2-pyrrolidone + water mixtures at various temperatures

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recommendations! Published in 2018 at "Journal of Molecular Liquids"

DOI: 10.1016/j.molliq.2018.01.043

Abstract: Abstract The trained versions of Yalkowsky and Jouyban-Acree models are proposed to predict solubility of drugs in binary aqueous mixtures of N-methyl-2-pyrrolidone (NMP) at various temperatures. To provide a full predictive model, the Abraham solvation… read more here.

Keywords: methyl pyrrolidone; trained models; generally trained; various temperatures ... See more keywords

Pre-Trained Models Based Receiver Design With Natural Redundancy for Chinese Characters

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recommendations! Published in 2022 at "IEEE Communications Letters"

DOI: 10.1109/lcomm.2022.3193644

Abstract: Pre-trained Models (PTMs) have reached the state-of-the-art (SOTA) on many Natural Language Processing (NLP) tasks and Computer Vision (CV) tasks, and are called the foundation models of artificial intelligence (AI) systems. In this letter, we… read more here.

Keywords: natural redundancy; trained models; receiver design; pre trained ... See more keywords

Transfer learning for improved electrocardiogram diagnosis of cardiac disease: exploring the potential of pre-trained models

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recommendations! Published in 2024 at "Bulletin of Electrical Engineering and Informatics"

DOI: 10.11591/eei.v13i5.7053

Abstract: Predicting the onset of cardiovascular disease (CVD) has been a hot topic for researchers for years, and recently, the concept of transfer learning has been gaining traction in this field. Transfer learning (TL) is a… read more here.

Keywords: pre trained; transfer learning; disease; cvd ... See more keywords

A comparative study of pre-trained models for image feature extraction in weather image classification using orange data mining

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recommendations! Published in 2025 at "Indonesian Journal of Electrical Engineering and Computer Science"

DOI: 10.11591/ijeecs.v37.i1.pp241-249

Abstract: This paper presents a detailed comparative analysis of pre-trained models for feature extraction in the domain of weather image classification. Utilizing the orange data mining toolkit, we investigated the effectiveness of six prominent pre-trained models-InceptionV3,… read more here.

Keywords: image classification; pre trained; image; weather image ... See more keywords

A Comprehensive Performance Analysis of Transfer Learning Optimization in Visual Field Defect Classification

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recommendations! Published in 2022 at "Diagnostics"

DOI: 10.3390/diagnostics12051258

Abstract: Numerous research have demonstrated that Convolutional Neural Network (CNN) models are capable of classifying visual field (VF) defects with great accuracy. In this study, we evaluated the performance of different pre-trained models (VGG-Net, MobileNet, ResNet,… read more here.

Keywords: trained models; accuracy; fine tuning; visual field ... See more keywords

TExCNN: Leveraging Pre-Trained Models to Predict Gene Expression from Genomic Sequences

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recommendations! Published in 2024 at "Genes"

DOI: 10.3390/genes15121593

Abstract: Background/Objectives: Understanding the relationship between DNA sequences and gene expression levels is of significant biological importance. Recent advancements have demonstrated the ability of deep learning to predict gene expression levels directly from genomic data. However,… read more here.

Keywords: gene expression; pre trained; dna sequences; trained models ... See more keywords

Assessment of Convolutional Neural Network Pre-Trained Models for Detection and Orientation of Cracks

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recommendations! Published in 2023 at "Materials"

DOI: 10.3390/ma16020826

Abstract: Failure due to cracks is a major structural safety issue for engineering constructions. Human examination is the most common method for detecting crack failure, although it is subjective and time-consuming. Inspection of civil engineering structures… read more here.

Keywords: crack; trained models; detection orientation; convolutional neural ... See more keywords