AIMC Topic: Research Design

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Addi-Reg: A Better Generalization-Optimization Tradeoff Regularization Method for Convolutional Neural Networks.

IEEE transactions on cybernetics
In convolutional neural networks (CNNs), generating noise for the intermediate feature is a hot research topic in improving generalization. The existing methods usually regularize the CNNs by producing multiplicative noise (regularization weights), c...

PDC: Pearl Detection with a Counter Based on Deep Learning.

Sensors (Basel, Switzerland)
Pearl detection with a counter (PDC) in a noncontact and high-precision manner is a challenging task in the area of commercial production. Additionally, sea pearls are considered to be quite valuable, so the traditional manual counting methods are no...

Machine Learning Assisted Prediction of Power Conversion Efficiency of All-Small Molecule Organic Solar Cells: A Data Visualization and Statistical Analysis.

Molecules (Basel, Switzerland)
Organic solar cells are famous for their cheap solution processing. Their industrialization needs fast designing of efficient materials. For this purpose, testing of large number of materials is necessary. Machine learning is a better option due to c...

A SuperLearner Approach to Predict Run-In Selection in Clinical Trials.

Computational and mathematical methods in medicine
A critical early step in a clinical trial is defining the study sample that appropriately represents the target population from which the sample will be drawn. Envisaging a "run-in" process in study design may accomplish this task; however, the tradi...

End-to-End Point Cloud Completion Network with Attention Mechanism.

Sensors (Basel, Switzerland)
We propose a conceptually simple, general framework and end-to-end approach to point cloud completion, entitled PCA-Net. This approach differs from the existing methods in that it does not require a "simple" network, such as multilayer perceptrons (M...

Semantic segmentation method of underwater images based on encoder-decoder architecture.

PloS one
With the exploration and development of marine resources, deep learning is more and more widely used in underwater image processing. However, the quality of the original underwater images is so low that traditional semantic segmentation methods obtai...

Implementation of a new Digi-HTA process for digital health technologies in Finland.

International journal of technology assessment in health care
OBJECTIVES: There has been a lack of health technology assessment (HTA) methods for novel digital health technologies (DHTs) such as mHealth, artificial intelligence, and robotics in Finland. The Digi-HTA method has been developed for this purpose. T...

Virtual high-count PET image generation using a deep learning method.

Medical physics
PURPOSE: Recently, deep learning-based methods have been established to denoise the low-count positron emission tomography (PET) images and predict their standard-count image counterparts, which could achieve reduction of injected dosage and scan tim...

Sports Deep Learning Method Based on Cognitive Human Behavior Recognition.

Computational intelligence and neuroscience
An in-depth learning-based approach is designed to develop the ability to recognize human behavior on the move. We introduce 3D residual structures and create 3D residual models. In order to get the most out of the data relationship of several consec...

A new fuzzy rule based multi-objective optimization method for cross-scale injection molding of protein electrophoresis microfluidic chips.

Scientific reports
Injection molding is one of the most promising technologies for the large-scale production and application of polymeric microfluidic chips. The multi-objective optimization of injection molding process for substrate and cover plate on protein electro...