| Publication |
Sentence |
Publish Date |
Extraction Date |
Species |
| Hua Ji. Application of multi-attribute decision-making combined with BERT-CNN model in the image construction of ice and snow tourism destination. Scientific reports. vol 15. issue 1. 2025-03-28. PMID:40148433. |
the study innovatively designs a text feature extraction model based on the bidirectional encoder representations from transformers (bert)-convolutional neural network (cnn). |
2025-03-28 |
2025-03-30 |
Not clear |
| Jilong Bian, Hao Lu, Limin Wei, Yang Li, Guohua Wan. Relational similarity-based graph contrastive learning for DTI prediction. Briefings in bioinformatics. vol 26. issue 2. 2025-03-24. PMID:40127181. |
the results demonstrate that combining the relational features obtained by graph contrastive learning with the structural ones extracted by d-mpnn and cnn enhances feature representation ability, thereby improving dti prediction performance. |
2025-03-24 |
2025-03-27 |
Not clear |
| Hulin Kuang, Yahui Wang, Xianzhen Tan, Jialin Yang, Jiarui Sun, Jin Liu, Wu Qiu, Jingyang Zhang, Jiulou Zhang, Chunfeng Yang, Jianxin Wang, Yang Che. LW-CTrans: A lightweight hybrid network of CNN and Transformer for 3D medical image segmentation. Medical image analysis. vol 102. 2025-03-19. PMID:40107117. |
therefore, we design a novel lightweight hybrid network that combines the strengths of cnn and transformers (lw-ctrans) and can boost the global and local representation capability at different stages. |
2025-03-19 |
2025-03-22 |
Not clear |
| Jingdong Zhou, Chongyuan Lian, Xiaoyong Lan, Xue Shi, Lan Wang, Nan Yan, Yi Gu. TAU-DI Net: A Multi-Scale Convolutional Network Combining Prob-Sparse Attention for EEG-based Depression Identification. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. vol 2024. 2025-03-05. PMID:40039164. |
this method conducts the structure, which combines frequency-periodic transformation and multi-scale cnn to extract multi-frequency information representations from the most significant and least significant frequencies. |
2025-03-05 |
2025-03-07 |
Not clear |
| Guohua Huang, Jianyi Lyu, Qi Dai, Weihong Che. EVlncRNA-net: A dual-channel deep learning approach for accurate prediction of experimentally validated lncRNAs. International journal of biological macromolecules. 2025-03-05. PMID:40043997. |
this framework incorporates two representation learning modules: evlncrna-net (gcn) and evlncrna-net (cnn). |
2025-03-05 |
2025-03-08 |
mouse |
| Chen Li, Xianwei Zheng, Chuangquan Chen, Zicong Deng, Yiqing Sh. Tiny Data Is Sufficient: A Generalizable CNN Architecture for Temporal Domain Long Sequence Identification. IEEE transactions on neural networks and learning systems. vol PP. 2025-03-03. PMID:40030343. |
the generic cnn implements customizable hyper-convolutional operations through non-linear convolvers, thereby enhancing feature representation effectiveness and significantly improving accuracy. |
2025-03-03 |
2025-03-14 |
Not clear |
| Qinglie Yua. Building rooftop extraction from high resolution aerial images using multiscale global perceptron with spatial context refinement. Scientific reports. vol 15. issue 1. 2025-02-22. PMID:39987354. |
to address these issues, this study developed a multi-scale global perceptron network based on transformer and cnn using novel encoder-decoders for enhancing contextual representation of buildings. |
2025-02-22 |
2025-02-25 |
Not clear |
| Jasmine A Moore, Chris Kang, Vibujithan Vigneshwaran, Emma A M Stanley, Ashar Memon, Matthias Wilms, Nils D Forker. Towards realistic simulation of disease progression in the visual cortex with CNNs. Scientific reports. vol 15. issue 1. 2025-02-19. PMID:39972104. |
therefore, we examine object recognition and internal representations of a cnn under neurodegeneration and neuroplasticity conditions simulated through synaptic weight decay and retraining. |
2025-02-19 |
2025-02-23 |
Not clear |
| Hyeonsu Lee, Dongmin Shi. Beyond Information Distortion: Imaging Variable-Length Time Series Data for Classification. Sensors (Basel, Switzerland). vol 25. issue 3. 2025-02-13. PMID:39943260. |
to evaluate our representation without relying on a powerful vision model as a backbone, we employ a straightforward lenet-like 2d cnn model. |
2025-02-13 |
2025-02-15 |
human |
| Zongping Lin, Jing Yang, Yabin Lian, Yanhong Chen, Zhonghui Huang, Kexin Nin. Optimization design of cross border intelligent marketing management model based on multi layer perceptron-grey wolf optimization convolutional neural network. Scientific reports. vol 15. issue 1. 2025-02-11. PMID:39934359. |
firstly, a dual path deep network structure was designed, in which one path was modeled using a multi-layer perceptron (mlp) to extract user interest features based on historical interaction ratings; another path utilizes convolutional neural networks (cnn) to extract semantic features from user label information and construct item feature representations. |
2025-02-11 |
2025-02-14 |
Not clear |
| Zi-Feng Zhou, Dong Huang, Chang-Dong Wan. Pyramid contrastive learning for clustering. Neural networks : the official journal of the International Neural Network Society. vol 185. 2025-02-07. PMID:39919524. |
to bridge the gap between the cnn (for capturing local information) and the transformer (for reflecting global dependencies), a mixed cnn-transformer based encoder is utilized as the backbone, whose cnn-transformer blocks are further divided into four stages, thus giving rise to a pyramid of multi-stage feature representations. |
2025-02-07 |
2025-02-10 |
Not clear |
| Ki Wook Lee, Nhat Truong Pham, Hye Jung Min, Hyun Woo Park, Ji Won Lee, Han-En Lo, Na Young Kwon, Jimin Seo, Illia Shaginyan, Heeje Cho, Leyi Wei, Balachandran Manavalan, Young-Jun Jeo. DOGpred: A Novel Deep Learning Framework for Accurate Identification of Human O-linked Threonine Glycosylation Sites. Journal of molecular biology. 2025-02-03. PMID:39900285. |
subsequently, we designed a stacked convolutional neural network (cnn) module to learn spatial feature representations from cfds and a stacked recurrent neural network (rnn) module to learn temporal feature representations from plm-based embeddings. |
2025-02-03 |
2025-02-06 |
human |
| Sotiris Chatzimiltis, Michalis Agathocleous, Vasilis J Promponas, Chris Christodoulo. Post-processing enhances protein secondary structure prediction with second order deep learning and embeddings. Computational and structural biotechnology journal. vol 27. 2025-01-27. PMID:39866664. |
in this paper, we deploy a convolutional neural network (cnn) trained with the subsampled hessian newton (shn) method (a hessian free optimisation variant), with a two- dimensional input representation of embeddings extracted from a language model pretrained with protein sequences. |
2025-01-27 |
2025-01-29 |
Not clear |
| Kainat Khan, Rahul Katary. MCBERT: A Multi-Modal Framework for the Diagnosis of Autism Spectrum Disorder. Biological psychology. 2024-12-26. PMID:39722324. |
in this paper, we developed a novel multimodal asd diagnosis architecture, referred to as multi-head cnn with bert (mcbert), which integrates bidirectional encoder representations from transformers (bert) for meta-features and a multi-head convolutional neural network (mcnn) for the brain image modality. |
2024-12-26 |
2024-12-29 |
Not clear |
| Anna-Katharina Meißner, Tobias Blau, David Reinecke, Gina Fürtjes, Lili Leyer, Nina Müller, Niklas von Spreckelsen, Thomas Stehle, Abdulkader Al Shugri, Reinhard Büttner, Roland Goldbrunner, Marco Timmer, Volker Neuschmeltin. Image Quality Assessment and Reliability Analysis of Artificial Intelligence-Based Tumor Classification of Stimulated Raman Histology of Tumor Biobank Samples. Diagnostics (Basel, Switzerland). vol 14. issue 23. 2024-12-17. PMID:39682609. |
due to the relatively low number of rare tumor representations in cnn training datasets, a valid prediction of rarer entities remains limited. |
2024-12-17 |
2024-12-21 |
Not clear |
| Bei Gong, Ida Puteri Mahsan, Junhua Xia. Federated learning-driven collaborative recommendation system for multi-modal art analysis and enhanced recommendations. PeerJ. Computer science. vol 10. 2024-12-09. PMID:39650398. |
this system uses pre-trained convolutional neural networks (cnn) and bidirectional encoder representation from transformers (bert) models to extract features from image and text data. |
2024-12-09 |
2024-12-12 |
Not clear |
| Igor V Tetko, Ruud van Deursen, Guillaume Godi. Be aware of overfitting by hyperparameter optimization! Journal of cheminformatics. vol 16. issue 1. 2024-12-09. PMID:39654058. |
we also extended the previous analysis by adding a representation learning method based on natural language processing of smiles called transformer cnn. |
2024-12-09 |
2024-12-12 |
Not clear |
| Vinay Priy Mishra, Yogendra Narain Singh, Feroz Khan, Malay Kishore Dutt. SeqDPI: A 1D-CNN approach for predicting binding affinity of kinase inhibitors. Journal of computational chemistry. vol 46. issue 1. 2024-12-07. PMID:39644133. |
the proposed seqdpi model extract the relevant drug and protein features from the one dimensional sequential representation of the dataset considered using optimized cnn networks that deploy convolutions on varying length of amino acid subsequence's to capture hidden pattern, the convolved drug- protein features obtained are then used as an input to l2 penalized feed forward neural network which matches the local residue patterns in protein classes with molecular fingerprints of drugs to predict the binding strength for all drug target pairs. |
2024-12-07 |
2024-12-10 |
Not clear |
| Shumei Ding, Jia Zheng, Cangzhi Ji. DeepMEns: an ensemble model for predicting sgRNA on-target activity based on multiple features. Briefings in functional genomics. 2024-11-11. PMID:39528429. |
the first part uses one-hot encoding, wherein 0-1 representation of the secondary structure is used as the input to the convolutional neural network (cnn) with transformer encoder. |
2024-11-11 |
2024-11-17 |
Not clear |
| Yun Wang, Longguang Wang, Kunhong Li, Yongjian Zhang, Dapeng Oliver Wu, Yulan Gu. Cost Volume Aggregation in Stereo Matching Revisited: A Disparity Classification Perspective. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. vol PP. 2024-11-11. PMID:39527433. |
with the help of homogeneous region representations, efficient and informative cost aggregation can be achieved with only a shallow 3d cnn. |
2024-11-11 |
2024-11-17 |
Not clear |