|
|
|
Shurong Peng, Lijuan Guo, Yuanshu Li, Haoyu Huang, Jiayi Peng and Xiaoxu Liu
The allocation of biogas between power generation and heat supply in traditional kitchen waste power generation system is unreasonable; for this reason, a biogas prediction method based on feature selection and heterogeneous model integration learning is...
ver más
|
|
|
|
|
|
Zeyu Xu, Wenbin Yu, Chengjun Zhang and Yadang Chen
In the era of noisy intermediate-scale quantum (NISQ) computing, the synergistic collaboration between quantum and classical computing models has emerged as a promising solution for tackling complex computational challenges. Long short-term memory (LSTM)...
ver más
|
|
|
|
|
|
Florin Leon, Marius Gavrilescu, Sabina-Adriana Floria and Alina Adriana Minea
This paper proposes a classification methodology aimed at identifying correlations between job ad requirements and transversal skill sets, with a focus on predicting the necessary skills for individual job descriptions using a deep learning model. The ap...
ver más
|
|
|
|
|
|
Ru Ye, Hongyan Xing and Xing Zhou
Addressing the limitations of manually extracting features from small maritime target signals, this paper explores Markov transition fields and convolutional neural networks, proposing a detection method for small targets based on an improved Markov tran...
ver más
|
|
|
|
|
|
Can Li, Hua Sun, Changhong Wang, Sheng Chen, Xi Liu, Yi Zhang, Na Ren and Deyu Tong
In order to safeguard image copyrights, zero-watermarking technology extracts robust features and generates watermarks without altering the original image. Traditional zero-watermarking methods rely on handcrafted feature descriptors to enhance their per...
ver más
|
|
|