AIMC Topic: Neural Networks, Computer

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The strength of Nesterov's accelerated gradient in boosting transferability of stealthy adversarial attacks.

PloS one
Deep neural networks have been shown to be highly vulnerable to adversarial examples-inputs crafted to mislead models by adding subtle, human-imperceptible perturbations. Transferability and stealthiness are two crucial metrics for evaluating adversa...

SVNC-Net: An optimized U-Net variant with 2D convolutions for lightweight 3D spleen segmentation.

PloS one
Accurate measurement of spleen volume is essential for the diagnosis of splenomegaly. While Computed Tomography (CT) is among the most reliable imaging modalities for this task, manual segmentation of the spleen is labor-intensive and impractical for...

Rapid analysis of chinese blanched chicken (Mahuang, Tuer, and Huangyou) based on volatile compounds and machine learning.

Food chemistry
To promote the intelligent development of the poultry industry, this study systematically analyzed volatile organic compounds (VOCs) in three Chinese Blanched Chicken (CBC) breeds (Mahuang, Tuer, and Huangyou) using gas chromatography-ion mobility sp...

Evolution of chromatographic modeling: From mechanistic models to hybrid models with physics-based deep learning.

Journal of chromatography. A
Hybrid modeling based on physics-based deep learning (PBDL) represents a transformative approach that unifies mechanistic understanding and data-driven learning, offering a pathway beyond the limitations of traditional chromatographic models. This re...

Deep Learning Model for Fast Determination of Equilibrium Dissociation Constants Using Biolayer Interferometry Sensorgrams.

Analytical chemistry
This paper explores the fusion model of deep learning with Bio-Layer Interferometry (BLI), a key detection method for biomolecular interactions. We constructed a convolutional neural network model capable of quickly predicting the value of the equili...

A machine-learning model to identify concurrent vascular disease in symptomatic patients with chronic obstructive pulmonary disease.

Annals of medicine
AIM/INTRODUCTION: Chronic obstructive pulmonary disease (COPD) is a complex, heterogeneous syndrome often accompanied by vascular diseases that worsen prognosis and quality of life. This study aimed to develop a machine learning model to identify con...

Full-scale representation guided network for retinal vessel segmentation.

BMC medical imaging
The U-Net architecture and its variants have remained state-of-the-art (SOTA) for retinal vessel segmentation over the past decade. In this study, we introduce a Full-Scale Guided Network (FSG-Net), where a novel feature representation module using m...

OCRNet a robust deep learning framework for alphanumeric character recognition to assist the visually impaired.

Scientific reports
Optical Character Recognition (OCR) is a part of transformative Artificial Intelligence (AI) technology which translates printed or handwritten texts into digital, machine-readable form. These OCR systems act as an assistive tool for visually impaire...

Wearable sensing for badminton stroke recognition with one-dimensional convolutional neural network.

Scientific reports
Motivated by the need to improve the performance of badminton players, various motion monitoring systems have been developed to assist coaches in badminton technique instruction. While traditional video or optical methods are limited to fixed scenari...

Hybrid deep learning framework for cardiovascular disease diagnosis and prognosis using GAN, LSTM, GRU, VARMA, and deep DynaQ network.

Scientific reports
Cardiovascular diseases (CVDs) are a major cause of morbidity and mortality worldwide. Effective CVD treatment requires early and accurate diagnosis. CVD diagnosis and prognosis can be done using medical image analysis. In this paper, we propose a no...