|
|
|
|
|
Igor Paz, Bernard Willinger, Auguste Gires, Bianca Alves de Souza, Laurent Monier, Hervé Cardinal, Bruno Tisserand, Ioulia Tchiguirinskaia and Daniel Schertzer
Recent studies have highlighted the need for high resolution rainfall measurements for better modelling of urban and peri-urban catchment responses. In this work, we used a fully-distributed model called ?Multi-Hydro? to study small-scale rainfall variab...
ver más
|
|
|
|
|
|
|
|
|
|
|
Haoran Liu, Kehui Xu, Bin Li, Ya Han and Guandong Li
Machine learning classifiers have been rarely used for the identification of seafloor sediment types in the rapidly changing dredge pits for coastal restoration. Our study uses multiple machine learning classifiers to identify the sediment types of the C...
ver más
|
|
|
|
|
|
|
|
|
|
|
Andrea Momblanch, Ian P. Holman and Sanjay K. Jain
Global change is expected to have a strong impact in the Himalayan region. The climatic and orographic conditions result in unique modelling challenges and requirements. This paper critically appraises recent hydrological modelling applications in Himala...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jesus M. Torres Palenzuela, Luis González Vilas, Francisco M. Bellas, Elina Garet, África González-Fernández and Evangelos Spyrakos
The NW coast of the Iberian Peninsula is dominated by extensive shellfish farming, which places this region as a world leader in mussel production. Harmful algal blooms in the area frequent lead to lengthy harvesting closures threatening food security. T...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jiaming Bian, Ye Liu and Jun Chen
In recent times, remote sensing image super-resolution reconstruction technology based on deep learning has experienced rapid development. However, most algorithms in this domain concentrate solely on enhancing the super-resolution network?s performance ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jian Liu, Shihui Yu, Xuemei Liu, Guohang Lu, Zhenbo Xin and Jin Yuan
In-field in situ droplet deposition digitization is beneficial for obtaining feedback on spraying performance and precise spray control, the cost-effectiveness of the measurement system is crucial to its scalable application. However, the limitations of ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Lilai Jin, Sarah J. Higgins, James A. Thompson, Michael P. Strager, Sean E. Collins and Jason A. Hubbart
Saturated hydraulic conductivity (Ksat) is a hydrologic flux parameter commonly used to determine water movement through the saturated soil zone. Understanding the influences of land-use-specific Ksat on the model estimation error of water balance compon...
ver más
|
|
|
|
|
|
|
|
|
|
|
Huizhong Xiong, Xiaotong Gao, Ningyi Zhang, Haoxiong He, Weidong Tang, Yingqiu Yang, Yuqian Chen, Yang Jiao, Yihong Song and Shuo Yan
A novel deep learning model, DiffuCNN, is introduced in this paper, specifically designed for counting tobacco lesions in complex agricultural settings. By integrating advanced image processing techniques with deep learning methodologies, the model signi...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yong Liu, Xiaohui Yan, Wenying Du, Tianqi Zhang, Xiaopeng Bai and Ruichuan Nan
The current work proposes a novel super-resolution convolutional transposed network (SRCTN) deep learning architecture for downscaling daily climatic variables. The algorithm was established based on a super-resolution convolutional neural network with t...
ver más
|
|
|
|
|
|
|
|
|
|
|
Tianhao Gao, Meng Zhang, Yifan Zhu, Youjian Zhang, Xiangsheng Pang, Jing Ying and Wenming Liu
Classifying sports videos is complex due to their dynamic nature. Traditional methods, like optical flow and the Histogram of Oriented Gradient (HOG), are limited by their need for expertise and lack of universality. Deep learning, particularly Convoluti...
ver más
|
|
|
|
|
|