|
|
|
|
|
Ognjen Radovic,Srdan Marinkovic,Jelena Radojicic
Credit scoring attracts special attention of financial institutions. In recent years, deep learning methods have been particularly interesting. In this paper, we compare the performance of ensemble deep learning methods based on decision trees with the b...
ver más
|
|
|
|
|
|
|
|
|
|
|
Saeed Samadianfard, Salar Jarhan, Ely Salwana, Amir Mosavi, Shahaboddin Shamshirband and Shatirah Akib
Advancement in river flow prediction systems can greatly empower the operational river management to make better decisions, practices, and policies. Machine learning methods recently have shown promising results in building accurate models for river flow...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jiarui Xia and Yongshou Dai
Ground roll noise suppression is a crucial step in processing deep pre-stack seismic data. Recently, supervised deep learning methods have gained popularity in this field due to their ability to adaptively learn and extract powerful features. However, th...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jiwun Yoon, Sang-Yong Lee and Ji-Yong Lee
Humans share a similar body structure, but each individual possesses unique characteristics, which we define as one?s body type. Various classification methods have been devised to understand and assess these body types. Recent research has applied artif...
ver más
|
|
|
|
|
|
|
|
|
|
|
Giorgio Lazzarinetti, Riccardo Dondi, Sara Manzoni and Italo Zoppis
Solving combinatorial problems on complex networks represents a primary issue which, on a large scale, requires the use of heuristics and approximate algorithms. Recently, neural methods have been proposed in this context to find feasible solutions for r...
ver más
|
|
|
|
|
|
|
|
|
|
|
Luis M. de Campos, Juan M. Fernández-Luna, Juan F. Huete, Francisco J. Ribadas-Pena and Néstor Bolaños
In the context of academic expert finding, this paper investigates and compares the performance of information retrieval (IR) and machine learning (ML) methods, including deep learning, to approach the problem of identifying academic figures who are expe...
ver más
|
|
|
|
|
|
|
|
|
|
|
Hamed Raoofi, Asa Sabahnia, Daniel Barbeau and Ali Motamedi
Traditional methods of supervision in the construction industry are time-consuming and costly, requiring significant investments in skilled labor. However, with advancements in artificial intelligence, computer vision, and deep learning, these methods ca...
ver más
|
|
|
|
|
|
|
|
|
|
|
Luana Conte, Emanuele Rizzo, Tiziana Grassi, Francesco Bagordo, Elisabetta De Matteis and Giorgio De Nunzio
Pedigree charts remain essential in oncological genetic counseling for identifying individuals with an increased risk of developing hereditary tumors. However, this valuable data source often remains confined to paper files, going unused. We propose a co...
ver más
|
|
|
|
|
|
|
|
|
|
|
Xie Lian, Xiaolong Hu, Liangsheng Shi, Jinhua Shao, Jiang Bian and Yuanlai Cui
The parameters of the GR4J-CemaNeige coupling model (GR4neige) are typically treated as constants. However, the maximum capacity of the production store (parX1) exhibits time-varying characteristics due to climate variability and vegetation coverage chan...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yongen Lin, Dagang Wang, Tao Jiang and Aiqing Kang
Reliable streamflow forecasting is a determining factor for water resource planning and flood control. To better understand the strengths and weaknesses of newly proposed methods in streamflow forecasting and facilitate comparisons of different research ...
ver más
|
|
|
|
|
|