30   Artículos

 
en línea
Pilar Rosado-Rodrigo and Ferran Reverter    
In the context of a society saturated in images, convolutional neural networks (CNNs), pre-trained using from the visual information contained in many thousands of images, constitute a tool that is of great use in helping us to organize the visual herita... ver más
Revista: Big Data and Cognitive Computing    Formato: Electrónico

 
en línea
Zhiguo Liang, Lijun Zhang and Xizhe Wang    
Since failure of steam turbines occurs frequently and can causes huge losses for thermal plants, it is important to identify a fault in advance. A novel clustering fault diagnosis method for steam turbines based on t-distribution stochastic neighborhood ... ver más
Revista: Algorithms    Formato: Electrónico

 
en línea
James Simon Flynn, Cinzia Giannetti and Hessel Van Dijk    
In many manufacturing systems, anomaly detection is critical to identifying process errors and ensuring product quality. This paper proposes three semi-supervised solutions to detect anomalies in Direct Current (DC) Nut Runner engine assembly processes. ... ver más
Revista: AI    Formato: Electrónico

 
en línea
Noor Kamal Al-Qazzaz, Iyden Kamil Mohammed, Halah Kamal Al-Qazzaz, Sawal Hamid Bin Mohd Ali and Siti Anom Ahmad    
Countless women and men worldwide have lost their lives to breast cancer (BC). Although researchers from around the world have proposed various diagnostic methods for detecting this disease, there is still room for improvement in the accuracy and efficie... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Bardia Rafieian, Pedro Hermosilla and Pere-Pau Vázquez    
In data science and visualization, dimensionality reduction techniques have been extensively employed for exploring large datasets. These techniques involve the transformation of high-dimensional data into reduced versions, typically in 2D, with the aim ... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Tulsi Patel, Mark W. Jones and Thomas Redfern    
We present a novel approach to providing greater insight into the characteristics of an unlabelled dataset, increasing the efficiency with which labelled datasets can be created. We leverage dimension-reduction techniques in combination with autoencoders... ver más
Revista: Algorithms    Formato: Electrónico

 
en línea
Zhaoyang Tong, Shirui Zhang, Jingxin Yu, Xiaolong Zhang, Baijuan Wang and Wengang Zheng    
The growth and yield of crops are highly dependent on irrigation. Implementing irrigation plans that are tailored to the specific water requirements of crops can enhance crop yield and improve the quality of tomatoes. The mastery and prediction of transp... ver más
Revista: Agronomy    Formato: Electrónico

 
en línea
Sardar Mehboob Hussain, Domenico Buongiorno, Nicola Altini, Francesco Berloco, Berardino Prencipe, Marco Moschetta, Vitoantonio Bevilacqua and Antonio Brunetti    
Computer-aided diagnosis (CAD) systems can help radiologists in numerous medical tasks including classification and staging of the various diseases. The 3D tomosynthesis imaging technique adds value to the CAD systems in diagnosis and classification of t... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
L. G. Divyanth, D. S. Guru, Peeyush Soni, Rajendra Machavaram, Mohammad Nadimi and Jitendra Paliwal    
Applications of deep-learning models in machine visions for crop/weed identification have remarkably upgraded the authenticity of precise weed management. However, compelling data are required to obtain the desired result from this highly data-driven ope... ver más
Revista: Algorithms    Formato: Electrónico

 
en línea
Pranita Patil and Kevin Purcell    
Although deep learning has proven to be tremendously successful, the main issue is the dependency of its performance on the quality and quantity of training datasets. Since the quality of data can be affected by biases, a novel deep learning method based... ver más
Revista: Future Internet    Formato: Electrónico

« Anterior     Página: 1 de 2     Siguiente »