AIMC Topic: Semantics

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A Deep Learning-Based Semantic Segmentation Model Using MCNN and Attention Layer for Human Activity Recognition.

Sensors (Basel, Switzerland)
With the development of wearable devices such as smartwatches, several studies have been conducted on the recognition of various human activities. Various types of data are used, e.g., acceleration data collected using an inertial measurement unit se...

Deep learning based classification of multi-label chest X-ray images via dual-weighted metric loss.

Computers in biology and medicine
-Thoracic disease, like many other diseases, can lead to complications. Existing multi-label medical image learning problems typically include rich pathological information, such as images, attributes, and labels, which are crucial for supplementary ...

HCTNet: A hybrid CNN-transformer network for breast ultrasound image segmentation.

Computers in biology and medicine
Automatic breast ultrasound image segmentation helps radiologists to improve the accuracy of breast cancer diagnosis. In recent years, the convolutional neural networks (CNNs) have achieved great success in medical image analysis. However, it exhibit...

A prefix and attention map discrimination fusion guided attention for biomedical named entity recognition.

BMC bioinformatics
BACKGROUND: The biomedical literature is growing rapidly, and it is increasingly important to extract meaningful information from the vast amount of literature. Biomedical named entity recognition (BioNER) is one of the key and fundamental tasks in b...

MedLexSp - a medical lexicon for Spanish medical natural language processing.

Journal of biomedical semantics
BACKGROUND: Medical lexicons enable the natural language processing (NLP) of health texts. Lexicons gather terms and concepts from thesauri and ontologies, and linguistic data for part-of-speech (PoS) tagging, lemmatization or natural language genera...

Ocean oil spill detection from SAR images based on multi-channel deep learning semantic segmentation.

Marine pollution bulletin
One of the major threats to marine ecosystems is pollution, particularly, that associated with the offshore oil and gas industry. Oil spills occur in the world's oceans every day, either as large-scale spews from drilling-rig or tanker accidents, or ...

DCSAU-Net: A deeper and more compact split-attention U-Net for medical image segmentation.

Computers in biology and medicine
Deep learning architecture with convolutional neural network achieves outstanding success in the field of computer vision. Where U-Net has made a great breakthrough in biomedical image segmentation and has been widely applied in a wide range of pract...

DeepMPF: deep learning framework for predicting drug-target interactions based on multi-modal representation with meta-path semantic analysis.

Journal of translational medicine
BACKGROUND: Drug-target interaction (DTI) prediction has become a crucial prerequisite in drug design and drug discovery. However, the traditional biological experiment is time-consuming and expensive, as there are abundant complex interactions prese...

PRA-Net: Part-and-Relation Attention Network for depression recognition from facial expression.

Computers in biology and medicine
Artificial intelligence methods are widely applied to depression recognition and provide an objective solution. Many effective automated methods for detecting depression use facial expressions, which are strong indicators to reflect psychiatric disor...

Error-Correcting Mean-Teacher: Corrections instead of consistency-targets applied to semi-supervised medical image segmentation.

Computers in biology and medicine
Semantic segmentation is an essential task in medical imaging research. Many powerful deep-learning-based approaches can be employed for this problem, but they are dependent on the availability of an expansive labeled dataset. In this work, we augmen...