| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| 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 |
| Lim Yi, Braulio Félix Gómez, Balakrishnan Ramalingam, Madan Mohan Rayguru, Mohan Rajesh Elara, Abdullah Aamir Haya. Self-reconfigurable robot vision pipeline for safer adaptation to varying pavements width and surface conditions. Scientific reports. vol 12. issue 1. 2022-08-25. PMID:36008439. |
the deeplabv3+ semantic segmentation algorithm was customized to identify the pavement type classification, an eight-layer cnn was proposed for pavement surface condition prediction. |
2022-08-25 |
2023-08-14 |
Not clear |
| Yang Li, Jia Ze Li, Qi Fan, Xin Li, Zhihong Wan. Psychological Education Health Assessment Problems Based on Improved Constructive Neural Network. Frontiers in psychology. vol 13. 2022-08-19. PMID:35983201. |
in order to better assess the mental health status, combining online text data and considering the problems of lexicon sparsity and small lexicon size in feature statistics of word frequency of the traditional linguistic inquiry and word count (liwc) dictionary, and combining the advantages of constructive neural network (cnn) convolutional neural network in contextual semantic extraction, a cnn-based mental health assessment method is proposed and evaluated with the measurement indicators in clpsych2017. |
2022-08-19 |
2023-08-14 |
Not clear |
| Degaga Wolde Feyisa, Taye Girma Debelee, Yehualashet Megersa Ayano, Samuel Rahimeto Kebede, Tariku Fekadu Assor. Lightweight Multireceptive Field CNN for 12-Lead ECG Signal Classification. Computational intelligence and neuroscience. vol 2022. 2022-08-18. PMID:35978890. |
in many detection tasks ranging from semantic segmentation of medical images to time-series data classification, multireceptive field cnn has improved performance. |
2022-08-18 |
2023-08-14 |
Not clear |
| Bin Fan, Junjie Zhou, Wensen Feng, Huayan Pu, Yuzhu Yang, Qingqun Kong, Fuchao Wu, Hongmin Li. Learning Semantic-aware Local Features for Long Term Visual Localization. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. vol PP. 2022-07-13. PMID:35830407. |
based on a state of the art cnn architecture for local feature learning, i.e., aslfeat, this paper leverages on the semantic information from an off-the-shelf semantic segmentation network to learn semantic-aware feature maps. |
2022-07-13 |
2023-08-14 |
human |
| Hangfeng Lin, Naiqing B. A CNN-Based Framework for Predicting Public Emotion and Multi-Level Behaviors Based on Network Public Opinion. Frontiers in psychology. vol 13. 2022-07-11. PMID:35814112. |
(2) to make the extracted feature semantic information more comprehensive, cnn and tf-idf-cor are combined to form an effective cor-cnn model for emotion and mental health prediction. |
2022-07-11 |
2023-08-14 |
Not clear |
| Mesfer Al Duhayyim, Hanan Abdullah Mengash, Radwa Marzouk, Mohamed K Nour, Hany Mahgoub, Fahd Althukair, Abdullah Mohame. Hybrid Rider Optimization with Deep Learning Driven Biomedical Liver Cancer Detection and Classification. Computational intelligence and neuroscience. vol 2022. 2022-07-11. PMID:35814569. |
in contrast to classical image-dependent "semantic" feature evaluation from human expertise, deep learning techniques could learn feature representation automatically from sample images using convolutional neural network (cnn). |
2022-07-11 |
2023-08-14 |
human |
| Muhammad Adeel Azam, Claudio Sampieri, Alessandro Ioppi, Pietro Benzi, Giorgio Gregory Giordano, Marta De Vecchi, Valentina Campagnari, Shunlei Li, Luca Guastini, Alberto Paderno, Sara Moccia, Cesare Piazza, Leonardo S Mattos, Giorgio Perett. Videomics of the Upper Aero-Digestive Tract Cancer: Deep Learning Applied to White Light and Narrow Band Imaging for Automatic Segmentation of Endoscopic Images. Frontiers in oncology. vol 12. 2022-06-20. PMID:35719939. |
this study is aimed to develop a cnn for automatic semantic segmentation of uadt cancer on endoscopic images. |
2022-06-20 |
2023-08-14 |
Not clear |