AIMC Topic: Neural Networks, Computer

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Promoter prediction in nannochloropsis based on densely connected convolutional neural networks.

Methods (San Diego, Calif.)
Promoter is a key DNA element located near the transcription start site, which regulates gene transcription by binding RNA polymerase. Thus, the identification of promoters is an important research field in synthetic biology. Nannochloropsis is an im...

Dynamic Auxiliary Soft Labels for decoupled learning.

Neural networks : the official journal of the International Neural Network Society
The long-tailed distribution in the dataset is one of the major challenges of deep learning. Convolutional Neural Networks have poor performance in identifying classes with only a few samples. For this problem, it has been proved that separating the ...

Convolutional neural network for automated peak detection in reversed-phase liquid chromatography.

Journal of chromatography. A
Although commercially available software provides options for automatic peak detection, visual inspection and manual corrections are often needed. Peak detection algorithms commonly employed require carefully written rules and thresholds to increase ...

Integration of Neighbor Topologies Based on Meta-Paths and Node Attributes for Predicting Drug-Related Diseases.

International journal of molecular sciences
Identifying new disease indications for existing drugs can help facilitate drug development and reduce development cost. The previous drug-disease association prediction methods focused on data about drugs and diseases from multiple sources. However,...

Upper and Lower Leaf Side Detection with Machine Learning Methods.

Sensors (Basel, Switzerland)
Recent studies have approached the identification of foliar plant diseases using artificial intelligence, but in these works, classification is achieved using only one side of the leaf. Phytopathology specifies that there are diseases that show simil...

Detection and Recognition of Pollen Grains in Multilabel Microscopic Images.

Sensors (Basel, Switzerland)
Analysis of pollen material obtained from the Hirst-type apparatus, which is a tedious and labor-intensive process, is usually performed by hand under a microscope by specialists in palynology. This research evaluated the automatic analysis of pollen...

Can Hyperspectral Imaging and Neural Network Classification Be Used for Ore Grade Discrimination at the Point of Excavation?

Sensors (Basel, Switzerland)
This work determines whether hyperspectral imaging is suitable for discriminating ore from waste at the point of excavation. A prototype scanning system was developed for this study. This system combined hyperspectral cameras and a three-dimensional ...

Identification of Characteristic Points in Multivariate Physiological Signals by Sensor Fusion and Multi-Task Deep Networks.

Sensors (Basel, Switzerland)
Identification of characteristic points in physiological signals, such as the peak of the R wave in the electrocardiogram and the peak of the systolic wave of the photopletismogram, is a fundamental step for the quantification of clinical parameters,...

Multi-Scale Attention Convolutional Network for Masson Stained Bile Duct Segmentation from Liver Pathology Images.

Sensors (Basel, Switzerland)
In clinical practice, the Ishak Score system would be adopted to perform the evaluation of the grading and staging of hepatitis according to whether portal areas have fibrous expansion, bridging with other portal areas, or bridging with central veins...

A union of deep learning and swarm-based optimization for 3D human action recognition.

Scientific reports
Human Action Recognition (HAR) is a popular area of research in computer vision due to its wide range of applications such as surveillance, health care, and gaming, etc. Action recognition based on 3D skeleton data allows simplistic, cost-efficient m...