AIMC Topic: Neural Networks, Computer

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Modelling vegetation land fragmentation in urban areas of Western Province, Sri Lanka using an Artificial Intelligence-based simulation technique.

PloS one
Vegetation land fragmentation has had numerous negative repercussions on sustainable development around the world. Urban planners are currently avidly investigating vegetation land fragmentation due to its effects on sustainable development. The lite...

Expectile Neural Networks for Genetic Data Analysis of Complex Diseases.

IEEE/ACM transactions on computational biology and bioinformatics
The genetic etiologies of common diseases are highly complex and heterogeneous. Classic methods, such as linear regression, have successfully identified numerous variants associated with complex diseases. Nonetheless, for most diseases, the identifie...

The role of capacity constraints in Convolutional Neural Networks for learning random versus natural data.

Neural networks : the official journal of the International Neural Network Society
Convolutional neural networks (CNNs) are often described as promising models of human vision, yet they show many differences from human abilities. We focus on a superhuman capacity of top-performing CNNs, namely, their ability to learn very large dat...

SP-GNN: Learning structure and position information from graphs.

Neural networks : the official journal of the International Neural Network Society
Graph neural network (GNN) is a powerful model for learning from graph data. However, existing GNNs may have limited expressive power, especially in terms of capturing adequate structural and positional information of input graphs. Structure properti...

Fast and robust parameter estimation with uncertainty quantification for the cardiac function.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Parameter estimation and uncertainty quantification are crucial in computational cardiology, as they enable the construction of digital twins that faithfully replicate the behavior of physical patients. Many model parameter...

Retention time prediction for small samples based on integrating molecular representations and adaptive network.

Journal of chromatography. B, Analytical technologies in the biomedical and life sciences
Retention time (RT) can provide orthogonal information different from that of mass spectrometry and contribute to identifying compounds. Many machine learning methods have been developed and applied to RT prediction. In application, the training data...

Use of semi-synthetic data for catheter segmentation improvement.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
In the era of data-driven machine learning algorithms, data is the new oil. For the most optimal results, datasets should be large, heterogeneous and, crucially, correctly labeled. However, data collection and labeling are time-consuming and labor-in...

Learning matrix factorization with scalable distance metric and regularizer.

Neural networks : the official journal of the International Neural Network Society
Matrix factorization has always been an encouraging field, which attempts to extract discriminative features from high-dimensional data. However, it suffers from negative generalization ability and high computational complexity when handling large-sc...

Early gastric cancer segmentation in gastroscopic images using a co-spatial attention and channel attention based triple-branch ResUnet.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The artificial segmentation of early gastric cancer (EGC) lesions in gastroscopic images remains a challenging task due to reasons including the diversity of mucosal features, irregular edges of EGC lesions and nuances betwe...

The potential of novel hybrid SBO-based long short-term memory network for prediction of dissolved oxygen concentration in successive points of the Savannah River, USA.

Environmental science and pollution research international
The accurate estimation of dissolved oxygen (DO) as an important water quality indicator can provide a basis for ensuring the preservation of the riverine ecosystem and designing proper water quality development plans. Therefore, this study aimed to ...