AIMC Topic: Attention

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3DCANN: A Spatio-Temporal Convolution Attention Neural Network for EEG Emotion Recognition.

IEEE journal of biomedical and health informatics Nov 10, 2022
Since electroencephalogram (EEG) signals can truly reflect human emotional state, emotion recognition based on EEG has turned into a critical branch in the field of artificial intelligence. Aiming at the disparity of EEG signals in various emotional ...
Humans Neural Networks, Computer Electroencephalography Attention Emotions Artificial Intelligence
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Multiple instance neural networks based on sparse attention for cancer detection using T-cell receptor sequences.

BMC bioinformatics Nov 8, 2022
Early detection of cancers has been much explored due to its paramount importance in biomedical fields. Among different types of data used to answer this biological question, studies based on T cell receptors (TCRs) are under recent spotlight due to ...
Neural Networks, Computer Machine Learning Humans ROC Curve Attention Neoplasms Receptors, Antigen, T-Cell
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Feature Pyramid U-Net with Attention for Semantic Segmentation of Forward-Looking Sonar Images.

Sensors (Basel, Switzerland) Nov 3, 2022
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...
Sound Attention Image Processing, Computer-Assisted Semantics Neural Networks, Computer
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Biomedical named entity recognition with the combined feature attention and fully-shared multi-task learning.

BMC bioinformatics Nov 3, 2022
BACKGROUND: Biomedical named entity recognition (BioNER) is a basic and important task for biomedical text mining with the purpose of automatically recognizing and classifying biomedical entities. The performance of BioNER systems directly impacts do...
Attention Neural Networks, Computer Data Mining Language
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Alpha-SGANet: A multi-attention-scale feature pyramid network combined with lightweight network based on Alpha-IoU loss.

PloS one Oct 27, 2022
The design of deep convolutional neural networks has resulted in significant advances and successes in the field of object detection. However, despite these achievements, the high computational and memory costs of such object detection networks on th...
Attention Neural Networks, Computer
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Embedding cognitive framework with self-attention for interpretable knowledge tracing.

Scientific reports Oct 20, 2022
Recently, deep neural network-based cognitive models such as deep knowledge tracing have been introduced into the field of learning analytics and educational data mining. Despite an accurate predictive performance of such models, it is challenging to...
Neural Networks, Computer Knowledge Humans Cognition Attention Learning
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Trainable Quaternion Extended Kalman Filter with Multi-Head Attention for Dead Reckoning in Autonomous Ground Vehicles.

Sensors (Basel, Switzerland) Oct 11, 2022
Extended Kalman filter (EKF) is one of the most widely used Bayesian estimation methods in the optimal control area. Recent works on mobile robot control and transportation systems have applied various EKF methods, especially for localization. Howeve...
Lasers Attention Robotics Bayes Theorem Algorithms
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MRBENet: A Multiresolution Boundary Enhancement Network for Salient Object Detection.

Computational intelligence and neuroscience Oct 10, 2022
Salient Object Detection (SOD) simulates the human visual perception in locating the most attractive objects in the images. Existing methods based on convolutional neural networks have proven to be highly effective for SOD. However, in some cases, th...
Visual Perception Semantics Humans Benchmarking Neural Networks, Computer Attention
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Modality attention fusion model with hybrid multi-head self-attention for video understanding.

PloS one Oct 6, 2022
Video question answering (Video-QA) is a subject undergoing intense study in Artificial Intelligence, which is one of the tasks which can evaluate such AI abilities. In this paper, we propose a Modality Attention Fusion framework with Hybrid Multi-he...
Information Storage and Retrieval Artificial Intelligence Communications Media Attention Algorithms
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Affinity Attention Graph Neural Network for Weakly Supervised Semantic Segmentation.

IEEE transactions on pattern analysis and machine intelligence Oct 4, 2022
Weakly supervised semantic segmentation is receiving great attention due to its low human annotation cost. In this paper, we aim to tackle bounding box supervised semantic segmentation, i.e., training accurate semantic segmentation models using bound...
Volatile Organic Compounds Semantics Supervised Machine Learning Attention Image Processing, Computer-Assisted Humans Algorithms Neural Networks, Computer
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