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Semantics

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Improved Monitoring of Wildlife Invasion through Data Augmentation by Extract-Append of a Segmented Entity.

Sensors (Basel, Switzerland)
Owing to the continuous increase in the damage to farms due to wild animals' destruction of crops in South Korea, various methods have been proposed to resolve these issues, such as installing electric fences and using warning lamps or ultrasonic wav...

Deep leaning-based ultra-fast stair detection.

Scientific reports
Staircases are some of the most common building structures in urban environments. Stair detection is an important task for various applications, including the environmental perception of exoskeleton robots, humanoid robots, and rescue robots and the ...

Deep learning recommendation algorithm based on semantic mining.

PloS one
This paper proposes Deep Semantic Mining based Recommendation (DSMR), which can extract user features and item attribute features more accurately by deeply mining the semantic information of review text and item description documents recommend. First...

A Review on Visual-SLAM: Advancements from Geometric Modelling to Learning-Based Semantic Scene Understanding Using Multi-Modal Sensor Fusion.

Sensors (Basel, Switzerland)
Simultaneous Localisation and Mapping (SLAM) is one of the fundamental problems in autonomous mobile robots where a robot needs to reconstruct a previously unseen environment while simultaneously localising itself with respect to the map. In particul...

A Novel Ground Metric for Optimal Transport-Based Chronological Age Estimation.

IEEE transactions on cybernetics
Label distribution learning (LDL) is the state-of-the-art approach to dealing with a number of real-world applications, such as chronological age estimation from a face image, where there is an inherent similarity among adjacent age labels. LDL takes...

Emotional Semantics-Preserved and Feature-Aligned CycleGAN for Visual Emotion Adaptation.

IEEE transactions on cybernetics
Thanks to large-scale labeled training data, deep neural networks (DNNs) have obtained remarkable success in many vision and multimedia tasks. However, because of the presence of domain shift, the learned knowledge of the well-trained DNNs cannot be ...

SOLO-SLAM: A Parallel Semantic SLAM Algorithm for Dynamic Scenes.

Sensors (Basel, Switzerland)
Simultaneous localization and mapping (SLAM) is a core technology for mobile robots working in unknown environments. Most existing SLAM techniques can achieve good localization accuracy in static scenes, as they are designed based on the assumption t...

COVID-19 Semantic Pneumonia Segmentation and Classification Using Artificial Intelligence.

Contrast media & molecular imaging
Coronavirus 2019 (COVID-19) has become a pandemic. The seriousness of COVID-19 can be realized from the number of victims worldwide and large number of deaths. This paper presents an efficient deep semantic segmentation network (DeepLabv3Plus). Initi...

Learning Across Tasks for Zero-Shot Domain Adaptation From a Single Source Domain.

IEEE transactions on pattern analysis and machine intelligence
Domain adaptation techniques learn transferable knowledge from a source domain to a target domain and train models that generalize well in the target domain. Unfortunately, a majority of the existing techniques are only applicable to scenarios that t...

Towards Uncovering the Intrinsic Data Structures for Unsupervised Domain Adaptation Using Structurally Regularized Deep Clustering.

IEEE transactions on pattern analysis and machine intelligence
Unsupervised domain adaptation (UDA) is to learn classification models that make predictions for unlabeled data on a target domain, given labeled data on a source domain whose distribution diverges from the target one. Mainstream UDA methods strive t...