AIMC Topic: Semantics

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Single-Shot Object Detection via Feature Enhancement and Channel Attention.

Sensors (Basel, Switzerland) Sep 10, 2022
Features play a critical role in computer vision tasks. Deep learning methods have resulted in significant breakthroughs in the field of object detection, but it is still an extremely challenging obstacle when an object is very small. In this work, w...
Neural Networks, Computer Attention Volatile Organic Compounds Semantics Records
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Research and Implementation of Text Generation Based on Text Augmentation and Knowledge Understanding.

Computational intelligence and neuroscience Sep 10, 2022
Text generation has always been limited by the lack of corpus data required for language model (LM) training and the low quality of the generated text. Researchers have proposed some solutions, but these solutions are often complex and will greatly i...
Language Natural Language Processing Semantics
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Multi-granularity heterogeneous graph attention networks for extractive document summarization.

Neural networks : the official journal of the International Neural Network Society Sep 5, 2022
Extractive document summarization is a fundamental task in natural language processing (NLP). Recently, several Graph Neural Networks (GNNs) are proposed for this task. However, most existing GNN-based models can neither effectively encode semantic n...
Neural Networks, Computer Language Natural Language Processing Semantics
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Automatic Segmentation of Standing Trees from Forest Images Based on Deep Learning.

Sensors (Basel, Switzerland) Sep 3, 2022
Semantic segmentation of standing trees is important to obtain factors of standing trees from images automatically and effectively. Aiming at the accurate segmentation of multiple standing trees in complex backgrounds, some traditional methods have s...
Deep Learning Image Processing, Computer-Assisted Forests Trees Semantics
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Global and Local Feature Reconstruction for Medical Image Segmentation.

IEEE transactions on medical imaging Aug 31, 2022
Learning how to capture long-range dependencies and restore spatial information of down-sampled feature maps are the basis of the encoder-decoder structure networks in medical image segmentation. U-Net based methods use feature fusion to alleviate th...
Neural Networks, Computer Image Processing, Computer-Assisted Semantics
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Item Relationship Graph Neural Networks for E-Commerce.

IEEE transactions on neural networks and learning systems Aug 31, 2022
In a modern e-commerce recommender system, it is important to understand the relationships among products. Recognizing product relationships-such as complements or substitutes-accurately is an essential task for generating better recommendation resul...
Neural Networks, Computer Algorithms Semantics Commerce
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Attention-Emotion-Enhanced Convolutional LSTM for Sentiment Analysis.

IEEE transactions on neural networks and learning systems Aug 31, 2022
Long short-term memory (LSTM) neural networks and attention mechanism have been widely used in sentiment representation learning and detection of texts. However, most of the existing deep learning models for text sentiment analysis ignore emotion's m...
Neural Networks, Computer Emotions Semantics Sentiment Analysis
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Siamese network with a depthwise over-parameterized convolutional layer for visual tracking.

PloS one Aug 31, 2022
Visual tracking is a fundamental research task in vision computer. It has broad application prospects, such as military defense and civil security. Visual tracking encounters many challenges in practical application, such as occlusion, fast motion an...
Neural Networks, Computer Algorithms Motion Semantics
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Image Semantic Segmentation of Underwater Garbage with Modified U-Net Architecture Model.

Sensors (Basel, Switzerland) Aug 30, 2022
Autonomous underwater garbage grasping and collection pose a great challenge to underwater robots. To assist underwater robots in locating and recognizing underwater garbage objects efficiently, a modified U-Net-based architecture consisting of a dee...
Deep Learning Image Processing, Computer-Assisted Semantics
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Computing semantic similarity of texts based on deep graph learning with ability to use semantic role label information.

Scientific reports Aug 30, 2022
We propose a deep graph learning approach for computing semantic textual similarity (STS) by using semantic role labels generated by a Semantic Role Labeling (SRL) system. SRL system output has significant challenges in dealing with graph-neural netw...
Neural Networks, Computer Semantics
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