AIMC Topic: Attention

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A Post-training Quantization Method for the Design of Fixed-Point-Based FPGA/ASIC Hardware Accelerators for LSTM/GRU Algorithms.

Computational intelligence and neuroscience May 11, 2022
Recurrent Neural Networks (RNNs) have become important tools for tasks such as speech recognition, text generation, or natural language processing. However, their inference may involve up to billions of operations and their large number of parameters...
Attention Algorithms Neural Networks, Computer Computers
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End-to-End Sentence-Level Multi-View Lipreading Architecture with Spatial Attention Module Integrated Multiple CNNs and Cascaded Local Self-Attention-CTC.

Sensors (Basel, Switzerland) May 9, 2022
Concomitant with the recent advances in deep learning, automatic speech recognition and visual speech recognition (VSR) have received considerable attention. However, although VSR systems must identify speech from both frontal and profile faces in re...
Attention Lipreading Speech Humans Language Neural Networks, Computer
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Salient Object Detection in the Deep Learning Era: An In-Depth Survey.

IEEE transactions on pattern analysis and machine intelligence May 5, 2022
As an essential problem in computer vision, salient object detection (SOD) has attracted an increasing amount of research attention over the years. Recent advances in SOD are predominantly led by deep learning-based solutions (named deep SOD). To ena...
Algorithms Superoxide Dismutase Deep Learning Attention
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Spatiotemporal Co-Attention Recurrent Neural Networks for Human-Skeleton Motion Prediction.

IEEE transactions on pattern analysis and machine intelligence May 5, 2022
Human motion prediction aims to generate future motions based on the observed human motions. Witnessing the success of Recurrent Neural Networks (RNN) in modeling sequential data, recent works utilize RNNs to model human-skeleton motions on the obser...
Humans Neural Networks, Computer Attention Skeleton Motion Algorithms
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Reporting details of neuroimaging studies on individual traits prediction: A literature survey.

NeuroImage May 2, 2022
Using machine-learning tools to predict individual phenotypes from neuroimaging data is one of the most promising and hence dynamic fields in systems neuroscience. Here, we perform a literature survey of the rapidly work on phenotype prediction in he...
Attention Connectome Phenotype Humans Algorithms Machine Learning
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MHA-CoroCapsule: Multi-Head Attention Routing-Based Capsule Network for COVID-19 Chest X-Ray Image Classification.

IEEE transactions on medical imaging May 2, 2022
The outbreak of COVID-19 threatens the lives and property safety of countless people and brings a tremendous pressure to health care systems worldwide. The principal challenge in the fight against this disease is the lack of efficient detection metho...
COVID-19 SARS-CoV-2 Neural Networks, Computer Humans Attention X-Rays Deep Learning
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Deep parameter-free attention hashing for image retrieval.

Scientific reports Apr 30, 2022
Deep hashing method is widely applied in the field of image retrieval because of its advantages of low storage consumption and fast retrieval speed. There is a defect of insufficiency feature extraction when existing deep hashing method uses the conv...
Attention Neural Networks, Computer Semantics
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MR-FPN: Multi-Level Residual Feature Pyramid Text Detection Network Based on Self-Attention Environment.

Sensors (Basel, Switzerland) Apr 27, 2022
With humanity entering the age of intelligence, text detection technology has been gradually applied in the industry. However, text detection in a complex background is still a challenging problem for researchers to overcome. Most of the current algo...
Semantics Records Attention Algorithms Neural Networks, Computer
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Attention-modulated multi-branch convolutional neural networks for neonatal brain tissue segmentation.

Computers in biology and medicine Apr 26, 2022
Accurate measurement of brain structures is essential for the evaluation of neonatal brain growth and development. The conventional methods use manual segmentation to measure brain tissues, which is very time-consuming and inefficient. Recent deep le...
Gray Matter Attention Image Processing, Computer-Assisted Magnetic Resonance Imaging Brain Neural Networks, Computer
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Clinical target segmentation using a novel deep neural network: double attention Res-U-Net.

Scientific reports Apr 25, 2022
We introduced Double Attention Res-U-Net architecture to address medical image segmentation problem in different medical imaging system. Accurate medical image segmentation suffers from some challenges including, difficulty of different interest obje...
Attention Neural Networks, Computer Algorithms Magnetic Resonance Imaging Image Processing, Computer-Assisted
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