AIMC Topic: Attention

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A deep learning based approach for automated plant disease classification using vision transformer.

Scientific reports Jul 7, 2022
Plant disease can diminish a considerable portion of the agricultural products on each farm. The main goal of this work is to provide visual information for the farmers to enable them to take the necessary preventive measures. A lightweight deep lear...
Attention Plant Diseases Deep Learning Endoscopy Neural Networks, Computer
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Solid Attenuation Components Attention Deep Learning Model to Predict Micropapillary and Solid Patterns in Lung Adenocarcinomas on Computed Tomography.

Annals of surgical oncology Jul 5, 2022
BACKGROUND: High-grade adenocarcinoma subtypes (micropapillary and solid) treated with sublobar resection have an unfavorable prognosis compared with those treated with lobectomy. We investigated the potential of incorporating solid attenuation compo...
Tomography, X-Ray Computed Deep Learning Retrospective Studies Attention Adenocarcinoma of Lung Adenocarcinoma Lung Neoplasms Humans
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UAT: Universal Attention Transformer for Video Captioning.

Sensors (Basel, Switzerland) Jun 25, 2022
Video captioning via encoder-decoder structures is a successful sentence generation method. In addition, using various feature extraction networks for extracting multiple features to obtain multiple kinds of visual features in the encoding process is...
Attention Neural Networks, Computer
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HARNU-Net: Hierarchical Attention Residual Nested U-Net for Change Detection in Remote Sensing Images.

Sensors (Basel, Switzerland) Jun 19, 2022
Change detection (CD) is a particularly important task in the field of remote sensing image processing. It is of practical importance for people when making decisions about transitional situations on the Earth's surface. The existing CD methods focus...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Remote Sensing Technology Algorithms Attention
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MTPA_Unet: Multi-Scale Transformer-Position Attention Retinal Vessel Segmentation Network Joint Transformer and CNN.

Sensors (Basel, Switzerland) Jun 17, 2022
Retinal vessel segmentation is extremely important for risk prediction and treatment of many major diseases. Therefore, accurate segmentation of blood vessel features from retinal images can help assist physicians in diagnosis and treatment. Convolut...
Fundus Oculi Neural Networks, Computer Retinal Vessels Image Processing, Computer-Assisted Attention
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AMB-Wnet: Embedding attention model in multi-bridge Wnet for exploring the mechanics of disease.

Gene expression patterns : GEP Jun 16, 2022
In recent years, progressive application of convolutional neural networks in image processing has successfully filtered into medical diagnosis. As a prerequisite for images detection and classification, object segmentation in medical images has attra...
Attention Neural Networks, Computer Image Processing, Computer-Assisted
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Deep Learning Approach to Impact Classification in Sensorized Panels Using Self-Attention.

Sensors (Basel, Switzerland) Jun 9, 2022
This paper proposes a new method of impact classification for a Structural Health Monitoring system through the use of Self-Attention, the central building block of the Transformer neural network. As a topical and highly promising neural network arch...
Arrhythmias, Cardiac Neural Networks, Computer Attention Electrocardiography Deep Learning Humans
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AL-Net: Attention Learning Network Based on Multi-Task Learning for Cervical Nucleus Segmentation.

IEEE journal of biomedical and health informatics Jun 3, 2022
Cervical nucleus segmentation is a crucial and challenging issue in automatic pathological diagnosis due to uneven staining, blurry boundaries, and adherent or overlapping nuclei in nucleus images. To overcome the limitation of current methods, we pr...
Neural Networks, Computer Female Humans Attention Cell Nucleus Cervix Uteri Image Processing, Computer-Assisted
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A convolution neural network with multi-level convolutional and attention learning for classification of cancer grades and tissue structures in colon histopathological images.

Computers in biology and medicine Jun 2, 2022
A clinically comparable Convolutional Neural Network framework-based technique for performing automated classification of cancer grades and tissue structures in hematoxylin and eosin-stained colon histopathological images is proposed in this paper. I...
Neural Networks, Computer Attention Colorectal Neoplasms Humans
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A Novel Method to Inspect 3D Ball Joint Socket Products Using 2D Convolutional Neural Network with Spatial and Channel Attention.

Sensors (Basel, Switzerland) May 31, 2022
Product defect inspections are extremely important for industrial manufacturing processes. It is necessary to develop a special inspection system for each industrial product due to their complexity and diversity. Even though high-precision 3D cameras...
Commerce Computer Systems Joints Neural Networks, Computer Attention
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