AIMC Topic: Pattern Recognition, Automated
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Protein Fold Recognition by Combining Support Vector Machines and Pairwise Sequence Similarity Scores.
IEEE/ACM transactions on computational biology and bioinformatics
Oct 7, 2021
Protein fold recognition is one of the most essential steps for protein structure prediction, aiming to classify proteins into known protein folds. There are two main computational approaches: one is the template-based method based on the alignment s...
Differentiable biology: using deep learning for biophysics-based and data-driven modeling of molecular mechanisms.
Nature methods
Oct 4, 2021
Deep learning using neural networks relies on a class of machine-learnable models constructed using 'differentiable programs'. These programs can combine mathematical equations specific to a particular domain of natural science with general-purpose, ...
An automated liver segmentation in liver iron concentration map using fuzzy c-means clustering combined with anatomical landmark data.
BMC medical imaging
Sep 28, 2021
BACKGROUND: To estimate median liver iron concentration (LIC) calculated from magnetic resonance imaging, excluded vessels of the liver parenchyma region were defined manually. Previous works proposed the automated method for excluding vessels from t...
A comparative study on image-based snake identification using machine learning.
Scientific reports
Sep 27, 2021
Automated snake image identification is important from different points of view, most importantly, snake bite management. Auto-identification of snake images might help the avoidance of venomous snakes and also providing better treatment for patients...
A Knowledge Graph Entity Disambiguation Method Based on Entity-Relationship Embedding and Graph Structure Embedding.
Computational intelligence and neuroscience
Sep 23, 2021
The purpose of knowledge graph entity disambiguation is to match the ambiguous entities to the corresponding entities in the knowledge graph. Current entity ambiguity elimination methods usually use the context information of the entity and its attri...
5G-enabled contactless multi-user presence and activity detection for independent assisted living.
Scientific reports
Sep 2, 2021
Wireless sensing is the state-of-the-art technique for next generation health activity monitoring. Smart homes and healthcare centres have a demand for multi-subject health activity monitoring to cater for future requirements. 5G-sensing coupled with...
DeepEthogram, a machine learning pipeline for supervised behavior classification from raw pixels.
eLife
Sep 2, 2021
Videos of animal behavior are used to quantify researcher-defined behaviors of interest to study neural function, gene mutations, and pharmacological therapies. Behaviors of interest are often scored manually, which is time-consuming, limited to few ...
Hybrid Gradient Descent Grey Wolf Optimizer for Optimal Feature Selection.
BioMed research international
Aug 28, 2021
Feature selection is the process of decreasing the number of features in a dataset by removing redundant, irrelevant, and randomly class-corrected data features. By applying feature selection on large and highly dimensional datasets, the redundant fe...
Computer vision based individual fish identification using skin dot pattern.
Scientific reports
Aug 19, 2021
Precision fish farming is an emerging concept in aquaculture research and industry, which combines new technologies and data processing methods to enable data-based decision making in fish farming. The concept is based on the automated monitoring of ...
Identifying resting state differences salient for resilience to chronic pain based on machine learning multivariate pattern analysis.
Psychophysiology
Aug 12, 2021
Studies have documented behavior differences between more versus less resilient adults with chronic pain (CP), but the presence and nature of underlying neurophysiological differences have received scant attention. In this study, we attempted to iden...
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