![PDF) Convolutional Neural Networks or Vision Transformers: Who Will Win the Race for Action Recognitions in Visual Data? PDF) Convolutional Neural Networks or Vision Transformers: Who Will Win the Race for Action Recognitions in Visual Data?](https://i1.rgstatic.net/publication/366987675_Convolutional_Neural_Networks_or_Vision_Transformers_Who_Will_Win_the_Race_for_Action_Recognitions_in_Visual_Data/links/63beb7467ecd35045c3d4540/largepreview.png)
PDF) Convolutional Neural Networks or Vision Transformers: Who Will Win the Race for Action Recognitions in Visual Data?
Big Data in Ehealthcare - Challenges and Perspectives | PDF | Apache Hadoop | Electronic Health Record
![Flexible and cost-effective cryptographic encryption algorithm for securing unencrypted database files at rest and in transit - Methods X Flexible and cost-effective cryptographic encryption algorithm for securing unencrypted database files at rest and in transit - Methods X](https://methods-x.com/cms/attachment/401a95b4-0427-4edf-8811-405a63edbb9b/ga1_lrg.jpg)
Flexible and cost-effective cryptographic encryption algorithm for securing unencrypted database files at rest and in transit - Methods X
![PDF) Neural Data-to-Text Generation Based on Small Datasets: Comparing the Added Value of Two Semi-Supervised Learning Approaches on Top of a Large Language Model PDF) Neural Data-to-Text Generation Based on Small Datasets: Comparing the Added Value of Two Semi-Supervised Learning Approaches on Top of a Large Language Model](https://i1.rgstatic.net/publication/362011663_Neural_Data-to-Text_Generation_Based_on_Small_Datasets_Comparing_the_Added_Value_of_Two_Semi-Supervised_Learning_Approaches_on_Top_of_a_Large_Language_Model/links/62d0db8728bd252b39f72f35/largepreview.png)
PDF) Neural Data-to-Text Generation Based on Small Datasets: Comparing the Added Value of Two Semi-Supervised Learning Approaches on Top of a Large Language Model
![PDF) A Text Mining Pipeline Using Active and Deep Learning Aimed at Curating Information in Computational Neuroscience PDF) A Text Mining Pipeline Using Active and Deep Learning Aimed at Curating Information in Computational Neuroscience](https://i1.rgstatic.net/publication/328974879_A_Text_Mining_Pipeline_Using_Active_and_Deep_Learning_Aimed_at_Curating_Information_in_Computational_Neuroscience/links/5bee2c724585150b2bba14b5/largepreview.png)
PDF) A Text Mining Pipeline Using Active and Deep Learning Aimed at Curating Information in Computational Neuroscience
![Development of a bioinformatics platform for analysis of quantitative transcriptomics and proteomics data: the OMnalysis [PeerJ] Development of a bioinformatics platform for analysis of quantitative transcriptomics and proteomics data: the OMnalysis [PeerJ]](https://dfzljdn9uc3pi.cloudfront.net/2021/12415/1/fig-4-full.png)
Development of a bioinformatics platform for analysis of quantitative transcriptomics and proteomics data: the OMnalysis [PeerJ]
![Simultaneous Prediction of Interaction Sites on the Protein and Peptide Sides of Complexes through Multilayer Graph Convolutional Networks | Journal of Chemical Information and Modeling Simultaneous Prediction of Interaction Sites on the Protein and Peptide Sides of Complexes through Multilayer Graph Convolutional Networks | Journal of Chemical Information and Modeling](https://pubs.acs.org/cms/10.1021/acs.jcim.3c00192/asset/images/large/ci3c00192_0001.jpeg)