AIMC Topic: Neural Networks, Computer

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Boosting the transferability of adversarial examples via stochastic serial attack.

Neural networks : the official journal of the International Neural Network Society
Deep neural networks (DNNs) are vulnerable to adversarial examples, which are crafted by imposing mild perturbation on clean ones. An intriguing property of adversarial examples is that they are efficient among different DNNs. Thus transfer-based att...

Convolutional neural network-based automatic classification for incomplete antibody reaction intensity in solid phase anti-human globulin test image.

Medical & biological engineering & computing
The precise classification of incomplete antibody reaction intensity (IARI) in hydrogel chromatography medium high density medium solid-phase Coombs test is essential for haemolytic disease screening. However, an automatic and contactless method is r...

Semantic Segmentation Dataset for AI-Based Quantification of Clean Mucosa in Capsule Endoscopy.

Medicina (Kaunas, Lithuania)
: Capsule endoscopy (CE) for bowel cleanliness evaluation primarily depends on subjective methods. To objectively evaluate bowel cleanliness, we focused on artificial intelligence (AI)-based assessments. We aimed to generate a large segmentation data...

Tree Trunk Recognition in Orchard Autonomous Operations under Different Light Conditions Using a Thermal Camera and Faster R-CNN.

Sensors (Basel, Switzerland)
In an orchard automation process, a current challenge is to recognize natural landmarks and tree trunks to localize intelligent robots. To overcome low-light conditions and global navigation satellite system (GNSS) signal interruptions under a dense ...

Real-Time Object Detection and Classification by UAV Equipped With SAR.

Sensors (Basel, Switzerland)
The article presents real-time object detection and classification methods by unmanned aerial vehicles (UAVs) equipped with a synthetic aperture radar (SAR). Two algorithms have been extensively tested: classic image analysis and convolutional neural...

Artificial Intelligent Deep Learning Molecular Generative Modeling of Scaffold-Focused and Cannabinoid CB2 Target-Specific Small-Molecule Sublibraries.

Cells
Design and generation of high-quality target- and scaffold-specific small molecules is an important strategy for the discovery of unique and potent bioactive drug molecules. To achieve this goal, authors have developed the deep-learning molecule gene...

Determining the anatomical site in knee radiographs using deep learning.

Scientific reports
An important quality criterion for radiographs is the correct anatomical side marking. A deep neural network is evaluated to predict the correct anatomical side in radiographs of the knee acquired in anterior-posterior direction. In this retrospectiv...

CNN-DDI: a learning-based method for predicting drug-drug interactions using convolution neural networks.

BMC bioinformatics
BACKGROUND: Drug-drug interactions (DDIs) are the reactions between drugs. They are compartmentalized into three types: synergistic, antagonistic and no reaction. As a rapidly developing technology, predicting DDIs-associated events is getting more a...

MCG-Net: End-to-End Fine-Grained Delineation and Diagnostic Classification of Cardiac Events From Magnetocardiographs.

IEEE journal of biomedical and health informatics
In this paper, we propose an end-to-end deep learning architecture, referred as MCG-Net, integrating convolutional neural network (CNN) with transformer-based global context block for fine-grained delineation and diagnostic classification of four car...

3D Graph-Connectivity Constrained Network for Hepatic Vessel Segmentation.

IEEE journal of biomedical and health informatics
Segmentation of hepatic vessels from 3D CT images is necessary for accurate diagnosis and preoperative planning for liver cancer. However, due to the low contrast and high noises of CT images, automatic hepatic vessel segmentation is a challenging ta...