| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| Sergey Shuvaev, Khue Tran, Khristina Samoilova, Cyrille Mascart, Alexei Koulako. DeepNose: An Equivariant Convolutional Neural Network Predictive Of Human Olfactory Percepts. ArXiv. 2024-12-23. PMID:39713803. |
to build these filters, we trained a convolutional neural network (cnn) to predict human olfactory percepts obtained from several semantic datasets. |
2024-12-23 |
2024-12-25 |
human |
| Jinze Huang, Yimin Li, Bo Meng, Yong Zhang, Yaoguang Wei, Xinhua Dai, Dong An, Yang Zhao, Xiang Fan. ProteoNet: A CNN-based framework for analyzing proteomics MS-RGB images. iScience. vol 27. issue 12. 2024-12-16. PMID:39679296. |
proteonet incorporates semantic partitioning, adaptive average pooling, and weighted factors into the convolutional neural network (cnn) model, thus enhancing data analysis accuracy. |
2024-12-16 |
2024-12-21 |
Not clear |
| Gowri L, Haris R, Sumathi M, S P Raj. Enhancing diabetic retinopathy and macular edema detection through multi scale feature fusion using deep learning model. Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie. 2024-12-16. PMID:39680112. |
methods this approach uses convolutional neural networks (cnn) and is designed to combine higher-level semantic inputs with low-level textural characteristics. |
2024-12-16 |
2024-12-21 |
Not clear |
| Bin Zhong, Runan Zhang, Shuixiang Luo, Jie Zhen. ILDIM-MFAM: interstitial lung disease identification model with multi-modal fusion attention mechanism. Frontiers in medicine. vol 11. 2024-12-03. PMID:39624040. |
convolutional neural network (cnn) is used to extract ct image features, bidirectional long short-term memory network (bi-lstm) model is used to learn temporal physiological metrics data under long-term dependency, and self-attention mechanism is used to encode textual semantic information in patient's self-reporting and medical prescriptions. |
2024-12-03 |
2024-12-06 |
Not clear |
| Kyle A Hasenstab, Lewis Hahn, Nick Chao, Albert Hsia. Simulating clinical features on chest radiographs for medical image exploration and CNN explainability using a style-based generative adversarial autoencoder. Scientific reports. vol 14. issue 1. 2024-10-18. PMID:39424900. |
we therefore propose semantic exploration and explainability using a style-based generative adversarial autoencoder network (see-gaan), an explainability framework that uses latent space manipulation to generate a sequence of synthetic images that semantically visualizes how clinical and cnn features manifest within medical images. |
2024-10-18 |
2024-10-21 |
Not clear |
| He Xue, Luo Yonggang, Liu Min, Li Li. A lighter hybrid feature fusion framework for polyp segmentation. Scientific reports. vol 14. issue 1. 2024-10-05. PMID:39369043. |
cthp combines the strengths of cnn, which excels at modeling local information, and transformer, which excels at modeling global semantics, to enhance segmentation accuracy. |
2024-10-05 |
2024-10-08 |
Not clear |
| Kuson Tuntiwong, Supan Tungjitkusolmun, Pattarapong Phasukki. Automated Crack Detection in Monolithic Zirconia Crowns Using Acoustic Emission and Deep Learning Techniques. Sensors (Basel, Switzerland). vol 24. issue 17. 2024-09-14. PMID:39275594. |
a new cnn image segmentation model, based on multi-class semantic segmentation using inception-resnet-v2, was developed. |
2024-09-14 |
2024-09-17 |
Not clear |
| Mühenad Bilal, Ranadheer Podishetti, Leonid Koval, Mahmoud A Gaafar, Daniel Grossmann, Markus Bregull. The Effect of Annotation Quality on Wear Semantic Segmentation by CNN. Sensors (Basel, Switzerland). vol 24. issue 15. 2024-08-10. PMID:39123824. |
the effect of annotation quality on wear semantic segmentation by cnn. |
2024-08-10 |
2024-08-13 |
Not clear |
| Aihua Ke, Jian Luo, Bo Ca. UNet-like network fused swin transformer and CNN for semantic image synthesis. Scientific reports. vol 14. issue 1. 2024-07-21. PMID:39033170. |
unet-like network fused swin transformer and cnn for semantic image synthesis. |
2024-07-21 |
2024-07-24 |
Not clear |
| Aihua Ke, Jian Luo, Bo Ca. UNet-like network fused swin transformer and CNN for semantic image synthesis. Scientific reports. vol 14. issue 1. 2024-07-21. PMID:39033170. |
semantic image synthesis approaches has been dominated by the modelling of convolutional neural networks (cnn). |
2024-07-21 |
2024-07-24 |
Not clear |
| Aihua Ke, Jian Luo, Bo Ca. UNet-like network fused swin transformer and CNN for semantic image synthesis. Scientific reports. vol 14. issue 1. 2024-07-21. PMID:39033170. |
to tackle this issue, we propose the sc-unet model, which is a unet-like network fused swin transformer and cnn for semantic image synthesis. |
2024-07-21 |
2024-07-24 |
Not clear |
| Lijia Zhi, Shaoyong Duan, Shaomin Zhan. Multiple semantic X-ray medical image retrieval using efficient feature vector extracted by FPN. Journal of X-ray science and technology. 2024-07-20. PMID:39031428. |
in this paper, we propose an effective deep convolutional neural network (cnn) model to extract concise feature vectors for multiple semantic x-ray medical image retrieval. |
2024-07-20 |
2024-07-24 |
Not clear |
| Zihong Xu, Ziyang Wan. MCV-UNet: a modified convolution & transformer hybrid encoder-decoder network with multi-scale information fusion for ultrasound image semantic segmentation. PeerJ. Computer science. vol 10. 2024-07-10. PMID:38983210. |
in this article, we introduce a novel hybrid network that synergistically combines convolutional neural networks (cnn) and vision transformers (vit) for ultrasound image semantic segmentation. |
2024-07-10 |
2024-07-12 |
Not clear |
| Nikolaos Detsikas, Nikolaos Mitianoudis, Ioannis Pratikaki. MResTNet: A Multi-Resolution Transformer Framework with CNN Extensions for Semantic Segmentation. Journal of imaging. vol 10. issue 6. 2024-06-26. PMID:38921602. |
mrestnet: a multi-resolution transformer framework with cnn extensions for semantic segmentation. |
2024-06-26 |
2024-06-29 |
Not clear |
| Tae Hoon Kim, Moez Krichen, Stephen Ojo, Meznah A Alamro, Gabriel Avelino Sampedr. TSSG-CNN: A Tuberculosis Semantic Segmentation-Guided Model for Detecting and Diagnosis Using the Adaptive Convolutional Neural Network. Diagnostics (Basel, Switzerland). vol 14. issue 11. 2024-06-19. PMID:38893700. |
this paper proposed a novel approach, named the tuberculosis segmentation-guided diagnosis model (tssg-cnn) for detecting tuberculosis, using a combined semantic segmentation and adaptive convolutional neural network (cnn) architecture. |
2024-06-19 |
2024-06-21 |
Not clear |
| Mohammad Siami, Tomasz Barszcz, Radoslaw Zimro. Advanced Image Analytics for Mobile Robot-Based Condition Monitoring in Hazardous Environments: A Comprehensive Thermal Defect Processing Framework. Sensors (Basel, Switzerland). vol 24. issue 11. 2024-06-19. PMID:38894210. |
this includes a semantic segmentation technique utilizing the pre-trained vgg16 cnn architecture for feature selection, followed by random forest (rf) and extreme gradient boosting (xgboost) classifiers for the prediction of the pixel class labels. |
2024-06-19 |
2024-06-21 |
Not clear |
| Maria Osório, Andreas Wicher. Promoting the Shift From Pixel-Level Correlations to Object Semantics Learning by Rethinking Computer Vision Benchmark Data Sets. Neural computation. 2024-05-22. PMID:38776966. |
the cnn poor performance on stanford dogs images underlines the disparity between deep learning and human visual perception, highlighting the need for models that learn object semantics. |
2024-05-22 |
2024-05-27 |
human |
| Yassine Oukdach, Anass Garbaz, Zakaria Kerkaou, Mohamed El Ansari, Lahcen Koutti, Ahmed Fouad El Ouafdi, Mouna Salihou. UViT-Seg: An Efficient ViT and U-Net-Based Framework for Accurate Colorectal Polyp Segmentation in Colonoscopy and WCE Images. Journal of imaging informatics in medicine. 2024-04-26. PMID:38671336. |
a vision transformer in the encoder section captures long-range semantic information, while a cnn module, integrating squeeze-excitation and dual attention mechanisms, captures low-level features, focusing on critical image regions. |
2024-04-26 |
2024-04-29 |
Not clear |
| Chao Ma, Yuan Gu, Ziyang Wan. TriConvUNeXt: A Pure CNN-Based Lightweight Symmetrical Network for Biomedical Image Segmentation. Journal of imaging informatics in medicine. 2024-04-23. PMID:38653912. |
specifically, a network block consisting of a depthwise cnn, a deformable cnn, and a dilated cnn is proposed to capture semantic feature information effectively while with low computational cost. |
2024-04-23 |
2024-04-26 |
Not clear |
| Leena Strauss, Arttu Junnila, Anni Wärri, Maria Manti, Yiwen Jiang, Eliisa Löyttyniemi, Elisabet Stener-Victorin, Marie K Lagerquist, Krisztina Kukoricza, Taija Heinosalo, Sami Blom, Matti Poutane. Consistent and effective method to define the mouse estrous cycle stage by deep learning based model. The Journal of endocrinology. 2024-04-09. PMID:38593833. |
the cnn was trained by supervised pixel-level multiclass semantic segmentation of image features from 171 hematoxylin-stained samples. |
2024-04-09 |
2024-04-12 |
mouse |