| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| Paveen Virameteeku. Paragraph-level attention based deep model for chapter segmentation. PeerJ. Computer science. vol 8. 2022-06-20. PMID:35721402. |
we first utilized a pre-trained xlnet model connected to a convolutional neural network (cnn) to extract the semantic meaning of each paragraph. |
2022-06-20 |
2023-08-14 |
Not clear |
| Juncheng Guo, Yuyan Wu, Lizhi Chen, Shangbin Long, Daqi Chen, Haibing Ouyang, Chunliang Zhang, Yadong Tang, Wenlong Wan. A perspective on the diagnosis of cracked tooth: imaging modalities evolve to AI-based analysis. Biomedical engineering online. vol 21. issue 1. 2022-06-15. PMID:35706023. |
what's more, ai-based crack detection and classification methods, especially the convolutional neural network (cnn)-based algorithms, including image classification (alexnet), object detection (yolo, faster-rcnn), semantic segmentation (u-net, segnet) are comprehensively reviewed. |
2022-06-15 |
2023-08-14 |
Not clear |
| Érika G de Assis, Zenilton K G do Patrocínio, Cristiane Neri Nobr. The Use of Convolutional Neural Networks in the Prediction of Invasive Ductal Carcinoma in Histological Images of Breast Cancer. Studies in health technology and informatics. vol 290. 2022-06-08. PMID:35673084. |
the method proposed in this work is a convolutional neural network (cnn) for visual semantic analysis of tumor regions for diagnostic support. |
2022-06-08 |
2023-08-14 |
Not clear |
| Jiang Liu, Yan Zhang, Danjv Lv, Jing Lu, Shanshan Xie, Jiali Zi, Yue Yin, Haifeng X. Birdsong classification based on ensemble multi-scale convolutional neural network. Scientific reports. vol 12. issue 1. 2022-05-23. PMID:35606386. |
however, as the number of network layers increases in traditional cnn, semantic information gradually becomes richer and detailed information disappears. |
2022-05-23 |
2023-08-13 |
Not clear |
| Jiayi Fan, Wentao Xie, Tiantian G. Automatic Gray Image Coloring Method Based on Convolutional Network. Computational intelligence and neuroscience. vol 2022. 2022-05-06. PMID:35515498. |
firstly, cnn is used to extract their semantic information, respectively. |
2022-05-06 |
2023-08-13 |
Not clear |
| Jiayi Fan, Wentao Xie, Tiantian G. Automatic Gray Image Coloring Method Based on Convolutional Network. Computational intelligence and neuroscience. vol 2022. 2022-05-06. PMID:35515498. |
during the transformation, images combined with semantic information are input into cnn model to obtain the content feature map of grayscale image and the style feature map of reference image. |
2022-05-06 |
2023-08-13 |
Not clear |
| Wei Wang, Yuxi Kang, Guanqun Liu, Xin Wan. SCU-Net: Semantic Segmentation Network for Learning Channel Information on Remote Sensing Images. Computational intelligence and neuroscience. vol 2022. 2022-04-20. PMID:35440946. |
on the basis of cdeconv, a convolutional neural network (cnn) with a channel attention mechanism for semantic segmentation is proposed as a channel upsampling network (scu-net). |
2022-04-20 |
2023-08-13 |
Not clear |
| Fred Fu, Angela Guenther, Ali Sakhdari, Trevor D McKee, Daniel Xi. Deep Learning Accurately Quantifies Plasma Cell Percentages on CD138-Stained Bone Marrow Samples. Journal of pathology informatics. vol 13. 2022-03-04. PMID:35242448. |
we trained a semantic segmentation-based convolutional neural network (cnn) using annotations of cd138+ and cd138- cells provided by one pathologist on small image patches of bone marrow and validated the cnn on an independent test set of image patches using annotations from two pathologists and a non-deep learning commercial software. |
2022-03-04 |
2023-08-13 |
Not clear |
| Jiachen Zhong, Junying Chen, Ajmal Mia. DualConv: Dual Convolutional Kernels for Lightweight Deep Neural Networks. IEEE transactions on neural networks and learning systems. vol PP. 2022-03-01. PMID:35230955. |
dualconv can be employed in any cnn model such as vgg-16 and resnet-50 for image classification, you only look once (yolo) and r-cnn for object detection, or fully convolutional network (fcn) for semantic segmentation. |
2022-03-01 |
2023-08-13 |
Not clear |
| José E Valdez-Rodríguez, Hiram Calvo, Edgardo Felipe-Riverón, Marco A Moreno-Armendári. Improving Depth Estimation by Embedding Semantic Segmentation: A Hybrid CNN Model. Sensors (Basel, Switzerland). vol 22. issue 4. 2022-02-26. PMID:35214571. |
improving depth estimation by embedding semantic segmentation: a hybrid cnn model. |
2022-02-26 |
2023-08-13 |
Not clear |
| José E Valdez-Rodríguez, Hiram Calvo, Edgardo Felipe-Riverón, Marco A Moreno-Armendári. Improving Depth Estimation by Embedding Semantic Segmentation: A Hybrid CNN Model. Sensors (Basel, Switzerland). vol 22. issue 4. 2022-02-26. PMID:35214571. |
to alleviate this problem, we propose the use of a semantic segmentation procedure that adds information to a depth estimator, in this case, a 3d convolutional neural network (cnn)-segmentation is coded as one-hot planes representing categories of objects. |
2022-02-26 |
2023-08-13 |
Not clear |
| José E Valdez-Rodríguez, Hiram Calvo, Edgardo Felipe-Riverón, Marco A Moreno-Armendári. Improving Depth Estimation by Embedding Semantic Segmentation: A Hybrid CNN Model. Sensors (Basel, Switzerland). vol 22. issue 4. 2022-02-26. PMID:35214571. |
particularly, we propose a hybrid 2d-3d cnn architecture capable of obtaining semantic segmentation and depth estimation at the same time. |
2022-02-26 |
2023-08-13 |
Not clear |
| David J Acunzo, Daniel M Low, Scott L Fairhal. Deep neural networks reveal topic-level representations of sentences in medial prefrontal cortex, lateral anterior temporal lobe, precuneus, and angular gyrus. NeuroImage. 2022-02-17. PMID:35176493. |
we constructed a topic-level sentence representations using the final layer of a convolutional neural network (cnn) trained to classify wikipedia sentences into broad semantic categories. |
2022-02-17 |
2023-08-13 |
human |
| D Sujatha, M Subramaniam, Chinnanadar Ramachandran Rene Robi. A new design of multimedia big data retrieval enabled by deep feature learning and Adaptive Semantic Similarity Function. Multimedia systems. 2022-02-14. PMID:35153387. |
here, the deep semantic feature extraction is performed by the convolutional neural network (cnn), which is again subjected to the semantic feature selection process by the new hybrid algorithm termed spider monkey-deer hunting optimization algorithm (sm-dhoa). |
2022-02-14 |
2023-08-13 |
spider |
| Ping Chen, JianYi Zhong, YueChao Zh. Intelligent Question Answering System by Deep Convolutional Neural Network in Finance and Economics Teaching. Computational intelligence and neuroscience. vol 2022. 2022-01-31. PMID:35096043. |
after being combined with the cnn algorithm, the language features of the sentence can be extracted more deeply, the semantic feature information can be captured more accurately from the sentence, and better performance can be maintained when processing more complex sentences. |
2022-01-31 |
2023-08-13 |
Not clear |
| Danny Chen, Wenzhong Yang, Liejun Wang, Sixiang Tan, Jiangzhaung Lin, Wenxiu B. PCAT-UNet: UNet-like network fused convolution and transformer for retinal vessel segmentation. PloS one. vol 17. issue 1. 2022-01-24. PMID:35073371. |
however, although cnn has achieved excellent performance, it cannot learn global and long-distance semantic information interaction well due to the local computing characteristics of convolution operation, which limits the development of medical image segmentation tasks. |
2022-01-24 |
2023-08-13 |
Not clear |
| Pan Liu, Yan Song, Mengyu Chai, Zelin Han, Yu Zhan. Swin-UNet++: A Nested Swin Transformer Architecture for Location Identification and Morphology Segmentation of Dimples on 2.25Cr1Mo0.25V Fractured Surface. Materials (Basel, Switzerland). vol 14. issue 24. 2021-12-24. PMID:34947098. |
however, with the development of the transformer in image recognition, the transformer-based neural network performs better on the learning of global and long-range semantic information than cnn and achieves higher prediction accuracy. |
2021-12-24 |
2023-08-13 |
Not clear |
| Ahmed Bahaa Farid, Enas Mohamed Fathy, Ahmed Sharaf Eldin, Laila A Abd-Elmegi. Software defect prediction using hybrid model (CBIL) of convolutional neural network (CNN) and bidirectional long short-term memory (Bi-LSTM). PeerJ. Computer science. vol 7. 2021-12-13. PMID:34901421. |
then, convolutional neural network (cnn) extracts the semantics of ast tokens. |
2021-12-13 |
2023-08-13 |
Not clear |
| Ziyang Wang, Irina Voiculesc. Quadruple Augmented Pyramid Network for Multi-class COVID-19 Segmentation via CT. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. vol 2021. 2021-12-11. PMID:34891865. |
quadruple augmented pyramid network (qap-net) not only enable cnn capture features from variation size of ct images, but also act as spatial inter-connections and down-sampling to transfer sufficient feature information for semantic segmentation. |
2021-12-11 |
2023-08-13 |
Not clear |
| Dimitrios Bellos, Mark Basham, Tony Pridmore, Andrew P Frenc. Temporal refinement of 3D CNN semantic segmentations on 4D time-series of undersampled tomograms using hidden Markov models. Scientific reports. vol 11. issue 1. 2021-12-07. PMID:34857791. |
temporal refinement of 3d cnn semantic segmentations on 4d time-series of undersampled tomograms using hidden markov models. |
2021-12-07 |
2023-08-13 |
Not clear |