| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| Jia Wu, Tingyu Yuan, Jiachen Zeng, Fangfang Go. A Medically Assisted Model for Precise Segmentation of Osteosarcoma Nuclei on Pathological Images. IEEE journal of biomedical and health informatics. vol PP. 2023-05-22. PMID:37216252. |
a multi-path semantic segmentation network combining transformer and cnn is used to segment images, and the degree of edge offset in the spatial domain is introduced into the loss function. |
2023-05-22 |
2023-08-14 |
Not clear |
| Malik Abdul Manan, Feng Jinchao, Tariq M Khan, Muhammad Yaqub, Shahzad Ahmed, Imran Shabir Chuha. Semantic segmentation of retinal exudates using a residual encoder-decoder architecture in diabetic retinopathy. Microscopy research and technique. 2023-05-17. PMID:37194727. |
in this paper, we present a comparison of deep convolutional neural network (cnn) architectures and propose a residual cnn with residual skip connections to reduce the parameter for the semantic segmentation of exudates in retinal images. |
2023-05-17 |
2023-08-14 |
Not clear |
| Songlin Dong, Yihong Gong, Jingang Shi, Miao Shang, Xiaoyu Tao, Xing Wei, Xiaopeng Hong, Tiangang Zho. Brain Cognition-Inspired Dual-Pathway CNN Architecture for Image Classification. IEEE transactions on neural networks and learning systems. vol PP. 2023-04-06. PMID:37022251. |
extensive experimental evaluations have revealed that the proposed cognets have achieved the state-of-the-art performance accuracies on all the six benchmark datasets and are very effective for overcoming the "texture bias" and the "semantic confusion" problems faced by many cnn models. |
2023-04-06 |
2023-08-14 |
human |
| Debanjan Konar, Siddhartha Bhattacharyya, Tapan K Gandhi, Bijaya K Panigrahi, Richard Jian. 3-D Quantum-Inspired Self-Supervised Tensor Network for Volumetric Segmentation of Medical Images. IEEE transactions on neural networks and learning systems. vol PP. 2023-04-06. PMID:37022399. |
the 3-d-qnet has achieved promising dice similarity (ds) as compared with the time-intensive supervised convolutional neural network (cnn)-based models, such as 3-d-unet, voxelwise residual network (voxresnet), dense-res-inception net (drinet), and 3-d-espnet, thereby showing a potential advantage of our self-supervised shallow network on facilitating semantic segmentation. |
2023-04-06 |
2023-08-14 |
Not clear |
| Shtwai Alsubai, Abdullah Alqahtani, Mohemmed Sh. Genetic hyperparameter optimization with Modified Scalable-Neighbourhood Component Analysis for breast cancer prognostication. Neural networks : the official journal of the International Neural Network Society. vol 162. 2023-03-13. PMID:36913821. |
this research utilizes deep cnn (deep convolutional neural network) and inception v3 for learning visual features which preserve neighbourhood outline in semantic space relying on nca (neighbourhood component analysis) criteria. |
2023-03-13 |
2023-08-14 |
Not clear |
| Vahid Asadpour, Eric J Puttock, Darios Getahun, Michael J Fassett, Fagen Xi. Automated placental abruption identification using semantic segmentation, quantitative features, SVM, ensemble and multi-path CNN. Heliyon. vol 9. issue 2. 2023-02-28. PMID:36852023. |
automated placental abruption identification using semantic segmentation, quantitative features, svm, ensemble and multi-path cnn. |
2023-02-28 |
2023-08-14 |
Not clear |
| 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 |
| Yuan Yang, Lin Zhang, Lei Ren, Xiaohan Wan. MMViT-Seg: A lightweight transformer and CNN fusion network for COVID-19 segmentation. Computer methods and programs in biomedicine. vol 230. 2023-01-27. PMID:36706618. |
the combination of cnn and transformers to complete the task of semantic segmentation has attracted intense research. |
2023-01-27 |
2023-08-14 |
human |
| Irma Dumbryte, Donatas Narbutis, Arturas Vailionis, Saulius Juodkazis, Mangirdas Malinauska. Revelation of microcracks as tooth structural element by X-ray tomography and machine learning. Scientific reports. vol 12. issue 1. 2022-12-28. PMID:36577779. |
a new cnn image segmentation model was trained based on "multiclass semantic segmentation using deeplabv3+" example and was implemented with "tensorflow". |
2022-12-28 |
2023-08-14 |
human |
| Aleena Nadeem, Muhammad Naveed, Muhammad Islam Satti, Hammad Afzal, Tanveer Ahmad, Ki-Il Ki. Depression Detection Based on Hybrid Deep Learning SSCL Framework Using Self-Attention Mechanism: An Application to Social Networking Data. Sensors (Basel, Switzerland). vol 22. issue 24. 2022-12-23. PMID:36560144. |
ultimately, a deep-learning-based hybrid sequence, semantic, context learning (sscl) classification framework with a self-attention mechanism is proposed that utilizes glove (pre-trained word embeddings) for feature extraction; lstm and cnn were used to capture the sequence and semantics of tweets; finally, the grus and self-attention mechanism were used, which focus on contextual and implicit information in the tweets. |
2022-12-23 |
2023-08-14 |
Not clear |
| Yuan Yao, Fang Wan, Wei Gao, Xingjia Pan, Zhiliang Peng, Qi Tian, Qixiang Y. TS-CAM: Token Semantic Coupled Attention Map for Weakly Supervised Object Localization. IEEE transactions on neural networks and learning systems. vol PP. 2022-11-23. PMID:36417732. |
based on our analysis, this is caused by cnn's intrinsic characteristics, which experiences difficulty to capture object semantics at long distances. |
2022-11-23 |
2023-08-14 |
Not clear |
| Akella S Narasimha Raju, Kayalvizhi Jayavel, T Rajalakshm. ColoRectalCADx: Expeditious Recognition of Colorectal Cancer with Integrated Convolutional Neural Networks and Visual Explanations Using Mixed Dataset Evidence. Computational and mathematical methods in medicine. vol 2022. 2022-11-21. PMID:36404909. |
the cadx system comprises five stages: convolutional neural networks (cnn), support vector machine (svm), long short-term memory (lstm), visual explanation such as gradient-weighted class activation mapping (grad-cam), and semantic segmentation phases. |
2022-11-21 |
2023-08-14 |
human |
| Akella S Narasimha Raju, Kayalvizhi Jayavel, T Rajalakshm. ColoRectalCADx: Expeditious Recognition of Colorectal Cancer with Integrated Convolutional Neural Networks and Visual Explanations Using Mixed Dataset Evidence. Computational and mathematical methods in medicine. vol 2022. 2022-11-21. PMID:36404909. |
after cnn and lstm, in advanced stage, malignancies are detected by using a better polyp recognition technique with grad-cam and semantic segmentation using u-net. |
2022-11-21 |
2023-08-14 |
human |
| Meghana Karri, Chandra Sekhara Rao Annavarapu, U Rajendra Achary. Explainable multi-module semantic guided attention based network for medical image segmentation. Computers in biology and medicine. vol 151. issue Pt A. 2022-11-06. PMID:36335811. |
in this paper, we involve substantial use of various attentions in a cnn model and present an explainable multi-module semantic guided attention based network (msga-net) for explainable and highly accurate medical image segmentation, which involves considering the most significant spatial regions, boundaries, scales, and channels. |
2022-11-06 |
2023-08-14 |
Not clear |
| Akella S Narasimha Raju, Kayalvizhi Jayavel, Thulasi Rajalakshm. Dexterous Identification of Carcinoma through ColoRectalCADx with Dichotomous Fusion CNN and UNet Semantic Segmentation. Computational intelligence and neuroscience. vol 2022. 2022-10-20. PMID:36262620. |
dexterous identification of carcinoma through colorectalcadx with dichotomous fusion cnn and unet semantic segmentation. |
2022-10-20 |
2023-08-14 |
human |
| Wenchao Zhang, Chong Fu, Yu Zheng, Fangyuan Zhang, Yanli Zhao, Chiu-Wing Sha. HSNet: A hybrid semantic network for polyp segmentation. Computers in biology and medicine. vol 150. 2022-10-18. PMID:36257278. |
for alleviating the bottlenecks, we investigate a hybrid semantic network (hsnet) that adopts both advantages of transformer and convolutional neural networks (cnn), aiming at improving polyp segmentation. |
2022-10-18 |
2023-08-14 |
Not clear |
| Hao Xu, Yuntian Chen, Dongxiao Zhan. Semantic Interpretation for Convolutional Neural Networks: What Makes a Cat a Cat? Advanced science (Weinheim, Baden-Wurttemberg, Germany). 2022-10-10. PMID:36216585. |
in this work, the framework of semantic explainable artificial intelligence (s-xai) is introduced, which utilizes a sample compression method based on the distinctive row-centered principal component analysis (pca) that is different from the conventional column-centered pca to obtain common traits of samples from the convolutional neural network (cnn), and extracts understandable semantic spaces on the basis of discovered semantically sensitive neurons and visualization techniques. |
2022-10-10 |
2023-08-14 |
cat |
| Hao Xu, Yuntian Chen, Dongxiao Zhan. Semantic Interpretation for Convolutional Neural Networks: What Makes a Cat a Cat? Advanced science (Weinheim, Baden-Wurttemberg, Germany). 2022-10-10. PMID:36216585. |
the experimental results demonstrate that s-xai is effective in providing a semantic interpretation for the cnn, and offers broad usage, including trustworthiness assessment and semantic sample searching. |
2022-10-10 |
2023-08-14 |
cat |
| Ying Qian, Jian Wu, Qian Zhan. CAT-CPI: Combining CNN and transformer to learn compound image features for predicting compound-protein interactions. Frontiers in molecular biosciences. vol 9. 2022-10-03. PMID:36188230. |
we use convolution neural network (cnn) to learn local features of molecular images and then use transformer encoder to capture the semantic relationships of these features. |
2022-10-03 |
2023-08-14 |
Not clear |
| Nicola Altini, Antonio Brunetti, Emilia Puro, Maria Giovanna Taccogna, Concetta Saponaro, Francesco Alfredo Zito, Simona De Summa, Vitoantonio Bevilacqu. NDG-CAM: Nuclei Detection in Histopathology Images with Semantic Segmentation Networks and Grad-CAM. Bioengineering (Basel, Switzerland). vol 9. issue 9. 2022-09-22. PMID:36135021. |
the first is the semantic segmentation obtained by the use of a cnn; then, the detection step is based on the calculation of local maxima of the grad-cam analysis evaluated on the nucleus class, allowing us to determine the positions of the nuclei centroids. |
2022-09-22 |
2023-08-14 |
Not clear |