AIMC Topic: Algorithms

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Incremental Unsupervised Domain-Adversarial Training of Neural Networks.

IEEE transactions on neural networks and learning systems
In the context of supervised statistical learning, it is typically assumed that the training set comes from the same distribution that draws the test samples. When this is not the case, the behavior of the learned model is unpredictable and becomes d...

Extending the Morphological Hit-or-Miss Transform to Deep Neural Networks.

IEEE transactions on neural networks and learning systems
While most deep learning architectures are built on convolution, alternative foundations such as morphology are being explored for purposes such as interpretability and its connection to the analysis and processing of geometric structures. The morpho...

A Bilevel Learning Model and Algorithm for Self-Organizing Feed-Forward Neural Networks for Pattern Classification.

IEEE transactions on neural networks and learning systems
Conventional artificial neural network (ANN) learning algorithms for classification tasks, either derivative-based optimization algorithms or derivative-free optimization algorithms work by training ANN first (or training and validating ANN) and then...

Using predictive machine learning models for drug response simulation by calibrating patient-specific pathway signatures.

NPJ systems biology and applications
The utility of pathway signatures lies in their capability to determine whether a specific pathway or biological process is dysregulated in a given patient. These signatures have been widely used in machine learning (ML) methods for a variety of appl...

Study on 3D Image Reconstruction Model of Sparring Action Based on Graph Neural Network (GNN).

Computational intelligence and neuroscience
With the advent of the information age, human demand for information is increasing day by day. The emergence of the concept of big data has triggered a new round of technological revolution, and visual information plays an important role in informati...

Image Quality Evaluation of Sanda Sports Video Based on BP Neural Network Perception.

Computational intelligence and neuroscience
In the special sports camera, there are subframes. A lens is composed of multiple frames. It will be unclear if a frame is cut out. The definition of video screenshots lies in the quality of video. To get clear screenshots, we need to find clear vide...

Multivariate Streamflow Simulation Using Hybrid Deep Learning Models.

Computational intelligence and neuroscience
Reliable and accurate streamflow simulation has a vital role in water resource development, mainly in agriculture, environment, domestic water supply, hydropower generation, flood control, and early warning systems. In this context, these days, deep ...

Optimization of Human Motion Recognition Information Processing System Based on GA-BP Neural Network Algorithm.

Computational intelligence and neuroscience
At present, there are some problems in the process of human motion recognition, such as poor timeliness and low fault tolerance rate. How to effectively identify the motion process accurately has become a hot spot in the optimization system. In the e...

Automated color detection in orchids using color labels and deep learning.

PloS one
The color of particular parts of a flower is often employed as one of the features to differentiate between flower types. Thus, color is also used in flower-image classification. Color labels, such as 'green', 'red', and 'yellow', are used by taxonom...

A Deep Learning-Based Model That Reduces Speed of Sound Aberrations for Improved In Vivo Photoacoustic Imaging.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Photoacoustic imaging (PAI) has attracted great attention as a medical imaging method. Typically, photoacoustic (PA) images are reconstructed via beamforming, but many factors still hinder the beamforming techniques in reconstructing optimal images i...