| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| Jianwei Lin, Jiatai Lin, Cheng Lu, Hao Chen, Huan Lin, Bingchao Zhao, Zhenwei Shi, Bingjiang Qiu, Xipeng Pan, Zeyan Xu, Biao Huang, Changhong Liang, Guoqiang Han, Zaiyi Liu, Chu Ha. CKD-TransBTS: Clinical Knowledge-Driven Hybrid Transformer with Modality-Correlated Cross-Attention for Brain Tumor Segmentation. IEEE transactions on medical imaging. vol PP. 2023-04-07. PMID:37027751. |
the proposed model inherits the strengths from both transformer and cnn with the local feature representation ability for precise lesion boundaries and long-range feature extraction for 3d volumetric images. |
2023-04-07 |
2023-08-14 |
Not clear |
| Zhenyu Lu, Yuelou Bian, Tingya Yang, Quanbo Ge, Yuanliang Wan. A New Siamese Heterogeneous Convolutional Neural Networks Based on Attention Mechanism and Feature Pyramid. IEEE transactions on cybernetics. vol PP. 2023-04-06. PMID:37021890. |
the tracker first uses a new fully cnn to extract image features, and introduces a channel attention mechanism in the feature extraction process to improve the representation ability of convolutional features. |
2023-04-06 |
2023-08-14 |
Not clear |
| Zhiliang Peng, Zonghao Guo, Wei Huang, Yaowei Wang, Lingxi Xie, Jianbin Jiao, Qi Tian, Qixiang Y. Conformer: Local Features Coupling Global Representations for Recognition and Detection. IEEE transactions on pattern analysis and machine intelligence. vol PP. 2023-04-06. PMID:37022836. |
conformer roots in feature coupling of cnn local features and transformer global representations under different resolutions in an interactive fashion. |
2023-04-06 |
2023-08-14 |
Not clear |
| Mengmeng Cui, Wei Wang, Kunbo Zhang, Zhenan Sun, Liang Wan. Pose-Appearance Relational Modeling for Video Action Recognition. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. vol PP. 2023-04-04. PMID:37015555. |
for the appearance stream, a spatial appearance cnn module is employed to extract the global appearance representation of the video sequence. |
2023-04-04 |
2023-08-14 |
human |
| Sha Huan, Limei Wu, Man Zhang, Zhaoyue Wang, Chao Yan. Radar Human Activity Recognition with an Attention-Based Deep Learning Network. Sensors (Basel, Switzerland). vol 23. issue 6. 2023-03-30. PMID:36991896. |
the doppler feature representation is obtained in sequence using the one-dimensional convolutional neural network (1d cnn) following the sliding window. |
2023-03-30 |
2023-08-14 |
human |
| Mats Svantesson, Håkan Olausson, Anders Eklund, Magnus Thordstei. Get a New Perspective on EEG: Convolutional Neural Network Encoders for Parametric t-SNE. Brain sciences. vol 13. issue 3. 2023-03-29. PMID:36979263. |
the principle of t-sne was used to train convolutional neural network (cnn) encoders to learn to produce both a high- and a low-dimensional representation, eliminating the need for feature engineering. |
2023-03-29 |
2023-08-14 |
Not clear |
| Mats Svantesson, Håkan Olausson, Anders Eklund, Magnus Thordstei. Get a New Perspective on EEG: Convolutional Neural Network Encoders for Parametric t-SNE. Brain sciences. vol 13. issue 3. 2023-03-29. PMID:36979263. |
the cnn encoders produced low-dimensional representations of the datasets with a structure that conformed well to the eeg characters and generalized to new data. |
2023-03-29 |
2023-08-14 |
Not clear |
| Mats Svantesson, Håkan Olausson, Anders Eklund, Magnus Thordstei. Get a New Perspective on EEG: Convolutional Neural Network Encoders for Parametric t-SNE. Brain sciences. vol 13. issue 3. 2023-03-29. PMID:36979263. |
compared to parametric t-sne for either a short-time fourier transform or wavelet representation of the datasets, the developed cnn encoders performed equally well in separating categories, as assessed by support vector machines. |
2023-03-29 |
2023-08-14 |
Not clear |
| Xin Xiao, Suyu Dong, Yang Yu, Yan Li, Guangyuan Yang, Zhaowen Qi. MAE-TransRNet: An improved transformer-ConvNet architecture with masked autoencoder for cardiac MRI registration. Frontiers in medicine. vol 10. 2023-03-27. PMID:36968818. |
in addition, concurrent spatial and channel squeeze and excitation (scse) module is embedded into the cnn structure, which also proves to be effective for extracting robust feature representations. |
2023-03-27 |
2023-08-14 |
human |
| Rita Fabiane Teixeira Gomes, Jean Schmith, Rodrigo Marques de Figueiredo, Samuel Armbrust Freitas, Giovanna Nunes Machado, Juliana Romanini, Vinicius Coelho Carrar. Use of Artificial Intelligence in the Classification of Elementary Oral Lesions from Clinical Images. International journal of environmental research and public health. vol 20. issue 5. 2023-03-11. PMID:36900902. |
the aim of this study was to perform the training and validation of a convolutional neural network (cnn)-based model to automatically classify six clinical representation categories of oral lesion images. |
2023-03-11 |
2023-08-14 |
Not clear |
| Junjun Fan, Jiajun Wen, Zhihui La. Myoelectric Pattern Recognition Using Gramian Angular Field and Convolutional Neural Networks for Muscle-Computer Interface. Sensors (Basel, Switzerland). vol 23. issue 5. 2023-03-11. PMID:36904918. |
to address this problem, a two-stage architecture, consisting of gramian angular field (gaf)-based 2d representation and convolutional neural network (cnn)-based classification (gaf-cnn), is proposed. |
2023-03-11 |
2023-08-14 |
Not clear |
| Jamie A O'Reilly, Jordan Wehrman, Aaron Carey, Jennifer Bedwin, Thomas Hourn, Fawad Asadi, Paul F Sowma. Neural correlates of face perception modeled with a convolutional recurrent neural network. Journal of neural engineering. 2023-03-10. PMID:36898147. |
we aimed to develop a computational model of visual erp generation to study this phenomenon which consisted of a three-dimensional convolutional neural network (cnn) connected to a recurrent neural network (rnn).
approach: the cnn provided image representation learning, complimenting sequence learning of the rnn for modeling visually-evoked potentials. |
2023-03-10 |
2023-08-14 |
human |
| Adrian Wheeldon, Alexander Ser. A study on the clusterability of latent representations in image pipelines. Frontiers in neuroinformatics. vol 17. 2023-03-06. PMID:36873564. |
here, we investigate the performance of various sequential clustering algorithms on latent representations generated by autoencoder and convolutional neural network (cnn) models. |
2023-03-06 |
2023-08-14 |
Not clear |
| Yuping Hu, Kechun Ya. Convolutional Neural Network Models Combined with Kansei Engineering in Product Design. Computational intelligence and neuroscience. vol 2023. 2023-03-03. PMID:36864929. |
the results show that the cnn model improves the "logical depth" of perceptual information of product design and gradually increases the abstraction degree of image information representation. |
2023-03-03 |
2023-08-14 |
Not clear |
| Walaa N Ismail, Hessah A Alsalamah, Mohammad Mehedi Hassan, Ebtesam Mohame. AUTO-HAR: An adaptive human activity recognition framework using an automated CNN architecture design. Heliyon. vol 9. issue 2. 2023-02-28. PMID:36852018. |
thus, the optimal cnn architecture representation can be found automatically because of its ability to overcome the limitations of human experience and thinking modes. |
2023-02-28 |
2023-08-14 |
human |
| Muhammet Fatih Aslan, Kadir Sabanc. A Novel Proposal for Deep Learning-Based Diabetes Prediction: Converting Clinical Data to Image Data. Diagnostics (Basel, Switzerland). vol 13. issue 4. 2023-02-25. PMID:36832284. |
this study converts numerical data into images based on the feature importance to use the robust representation of cnn models in early diabetes diagnosis. |
2023-02-25 |
2023-08-14 |
Not clear |
| Matthew F Wipperman, Galen Pogoncheff, Katrina F Mateo, Xuefang Wu, Yiziying Chen, Oren Levy, Andreja Avbersek, Robin R Deterding, Sara C Hamon, Tam Vu, Rinol Alaj, Olivier Harar. A pilot study of the Earable device to measure facial muscle and eye movement tasks among healthy volunteers. PLOS digital health. vol 1. issue 6. 2023-02-22. PMID:36812552. |
additionally, a convolutional neural network (cnn) was used to classify low-level representations of the raw bio-sensor data for each task, and model performance was correspondingly evaluated and compared directly to feature classification performance. |
2023-02-22 |
2023-08-14 |
human |
| Arsal Syed, Brendan Tran Morri. Semantic scene upgrades for trajectory prediction. Machine vision and applications. vol 34. issue 2. 2023-01-30. PMID:36712952. |
experimental results show that utilizing a fully segmented map, for explicit scene semantics, out performs other variants of scene representations (semantic and cnn embedding) for trajectory prediction tasks. |
2023-01-30 |
2023-08-14 |
Not clear |
| Franziska Hakansson, Dan Børge Jense. Automatic monitoring and detection of tail-biting behavior in groups of pigs using video-based deep learning methods. Frontiers in veterinary science. vol 9. 2023-01-30. PMID:36713870. |
two secondary frameworks were utilized, being a long short-term memory (lstm) network applied to sequences of image features (cnn-lstm), and a cnn applied to image representations of sequences (cnn-cnn). |
2023-01-30 |
2023-08-14 |
Not clear |
| Quoc Dang Vu, Kashif Rajpoot, Shan E Ahmed Raza, Nasir Rajpoo. Handcrafted Histological Transformer (H2T): Unsupervised representation of whole slide images. Medical image analysis. vol 85. 2023-01-26. PMID:36702037. |
to address this challenge, we present a handcrafted framework based on deep cnn for constructing holistic wsi-level representations. |
2023-01-26 |
2023-08-14 |
Not clear |