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Semantics

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Semantic segmentation method for myocardial contrast echocardiogram based on DeepLabV3+ deep learning architecture.

Mathematical biosciences and engineering : MBE
Myocardial contrast echocardiography (MCE) has been proposed as a method to assess myocardial perfusion for the detection of coronary artery diseases in a non-invasive way. As a critical step of automatic MCE perfusion quantification, myocardium segm...

Attention-enabled gated spiking neural P model for aspect-level sentiment classification.

Neural networks : the official journal of the International Neural Network Society
Gated spiking neural P (GSNP) model is a recently developed recurrent-like network, which is abstracted by nonlinear spiking mechanism of nonlinear spiking neural P systems. In this study, a modification of GSNP is combined with attention mechanism t...

Segmentation with mixed supervision: Confidence maximization helps knowledge distillation.

Medical image analysis
Despite achieving promising results in a breadth of medical image segmentation tasks, deep neural networks (DNNs) require large training datasets with pixel-wise annotations. Obtaining these curated datasets is a cumbersome process which limits the a...

Feature Pyramid U-Net with Attention for Semantic Segmentation of Forward-Looking Sonar Images.

Sensors (Basel, Switzerland)
Forward-looking sonar is a technique widely used for underwater detection. However, most sonar images have underwater noise and low resolution due to their acoustic properties. In recent years, the semantic segmentation model U-Net has shown excellen...

Semantic Terrain Segmentation in the Navigation Vision of Planetary Rovers-A Systematic Literature Review.

Sensors (Basel, Switzerland)
: The planetary rover is an essential platform for planetary exploration. Visual semantic segmentation is significant in the localization, perception, and path planning of the rover autonomy. Recent advances in computer vision and artificial intellig...

Caps Captioning: A Modern Image Captioning Approach Based on Improved Capsule Network.

Sensors (Basel, Switzerland)
In image captioning models, the main challenge in describing an image is identifying all the objects by precisely considering the relationships between the objects and producing various captions. Over the past few years, many methods have been propos...

Exploring Intra- and Inter-Video Relation for Surgical Semantic Scene Segmentation.

IEEE transactions on medical imaging
Automatic surgical scene segmentation is fundamental for facilitating cognitive intelligence in the modern operating theatre. Previous works rely on conventional aggregation modules (e.g., dilated convolution, convolutional LSTM), which only make use...

Deep Rating and Review Neural Network for Item Recommendation.

IEEE transactions on neural networks and learning systems
To alleviate the sparsity issue, many recommender systems have been proposed to consider the review text as the auxiliary information to improve the recommendation quality. Despite success, they only use the ratings as the ground truth for error back...

Explainable multi-module semantic guided attention based network for medical image segmentation.

Computers in biology and medicine
Automated segmentation of medical images is crucial for disease diagnosis and treatment planning. Medical image segmentation has been improved based on the convolutional neural networks (CNNs) models. Unfortunately, they are still limited by scenario...

Semantic Annotation of Experimental Methods in Analytical Chemistry.

Analytical chemistry
A major obstacle for reusing and integrating existing data is finding the data that is most relevant in a given context. The primary metadata resource is the scientific literature describing the experiments that produced the data. To stimulate the de...