201   Artículos

 
en línea
Minxing Dong, Jichao Yang, Yushan Fu, Tengfei Fu, Qing Zhao, Xuelei Zhang, Qinzeng Xu and Wenquan Zhang    
The soft coral order Alcyonacea is a common coral found in the deep sea and plays a crucial role in the deep-sea ecosystem. This study aims to predict the distribution of Alcyonacea in the western Pacific Ocean using four machine learning-based species d... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Alper Taner, Mahtem Teweldemedhin Mengstu, Kemal Çagatay Selvi, Hüseyin Duran, Ibrahim Gür and Nicoleta Ungureanu    
Having the advantages of speed, suitability and high accuracy, computer vision has been effectively utilized as a non-destructive approach to automatically recognize and classify fruits and vegetables, to meet the increased demand for food quality-sensin... ver más
Revista: Agriculture    Formato: Electrónico

 
en línea
Kalyan Chatterjee, M. Raju, N. Selvamuthukumaran, M. Pramod, B. Krishna Kumar, Anjan Bandyopadhyay and Saurav Mallik    
According to global data on visual impairment from the World Health Organization in 2010, an estimated 285 million individuals, including 39 million who are blind, face visual impairments. These individuals use non-contact methods such as voice commands ... ver más
Revista: Information    Formato: Electrónico

 
en línea
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
Revista: Information    Formato: Electrónico

 
en línea
Laura Lisso, John B. Lindsay and Aaron Berg    
Climate change research identifies risks to agriculture that will impact agricultural land suitability. To mitigate these impacts, agricultural growing regions will need to adapt, diversify, or shift in location. Various machine learning algorithms have ... ver más
Revista: Agronomy    Formato: Electrónico

 
en línea
Yanxi Zhao, Dengpan Xiao, Huizi Bai, Jianzhao Tang, De Li Liu, Yongqing Qi and Yanjun Shen    
The accuracy prediction for the crop yield is conducive to the food security in regions and/or nations. To some extent, the prediction model for crop yields combining the crop mechanism model with statistical regression model (SRM) can improve the timeli... ver más
Revista: Agriculture    Formato: Electrónico

 
en línea
Seongil Kim and Youngjin Park    
We present a straightforward approach for reconstructing 3D celadon models from a single 2D image. The celadon is a historical example of the surface of revolution. Our approach uses a surface of revolution technique to generate the basic shape of the ce... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Panagiotis Skondras, Panagiotis Zervas and Giannis Tzimas    
In this article, we investigate the potential of synthetic resumes as a means for the rapid generation of training data and their effectiveness in data augmentation, especially in categories marked by sparse samples. The widespread implementation of mach... ver más
Revista: Future Internet    Formato: Electrónico

 
en línea
Yik Kang Ang, Amin Talei, Izni Zahidi and Ali Rashidi    
Neuro-fuzzy systems (NFS), as part of artificial intelligence (AI) techniques, have become popular in modeling and forecasting applications in many fields in the past few decades. NFS are powerful tools for mapping complex associations between inputs and... ver más
Revista: Hydrology    Formato: Electrónico

 
en línea
Deepak Verma, Parveen Berwal, Mohammad Amir Khan, Raied Saad Alharbi, Faisal M. Alfaisal and Upaka Rathnayake    
The study of embankment breaching is not an easy practice, as it includes various parameters to meet the suitability of the design approach, especially when we consider it for the long term. Embankment breach studies generally include the prediction of d... ver más
Revista: Water    Formato: Electrónico

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