Results 111 to 120 of about 5,349,001 (214)

A hybrid approach of deep learning to forecast financial performance: from unsupervised to supervised

Systems Science & Control Engineering
The financial performance of a listed company is a common concern for shareholders, creditors, employees, securities analysts, and the government. Measuring and forecasting financial performance informs stakeholders about a company's overall well-being ...
Jiadong Teng
doaj   +1 more source

Boosted Convolutional Neural Networks [PDF]

Procedings of the British Machine Vision Conference 2016, 2016
Mohammad Moghimi, Serge J. Belongie, Mohammad J. Saberian, Jian Yang 0003, Nuno Vasconcelos, Li-Jia Li 0001   +5 more
openaire   +2 more sources

Application of deep learning for division of petroleum reservoirs

MATEC Web of Conferences, 2018
Traditional methods of dividing petroleum reservoirs are inefficient, and the accuracy of onehidden-layer BP neural network is not ideal when applied to dividing reservoirs.
Qin Yaqiong, Ye Zhaohui, Zhang Conghui
doaj   +1 more source

Understanding Convolutional Neural Networks

CoRR, 2016
Statistical Machine Learning Course Project at Carnegie Mellon ...
openaire   +2 more sources

On the Efficiency of Convolutional Neural Networks

CoRR
Since the breakthrough performance of AlexNet in 2012, convolutional neural networks (convnets) have grown into extremely powerful vision models. Deep learning researchers have used convnets to perform vision tasks with accuracy that was unachievable a decade ago. Confronted with the immense computation that convnets use, deep learning researchers also
openaire   +3 more sources

Crowd Density Estimation Using Deep Learning: A Convolutional Neural Network Approach for Real-time Monitoring [PDF]

Crowd density estimation is an essential aspect of public safety, urban management, and event monitoring. The emergence of deep learning techniques has revolutionized this domain by providing scalable, efficient, and accurate methods for estimating crowd
Jagriti, Singh, Khushi, Kawade
core  

Shearlet transform and convolutional neural network for histopathology images in breast cancer classification [PDF]

Breast cancer stands out as one of the global health threats, as it may cause death if improperly treated. Thus, detecting the illness at the early stage through precise diagnosis is important to prevent progression of tumors with effective treatments ...
Bakar, M. A. A., Alias, M. A., Rosli, N., Farid, M., Khairi, S. S. M., Bakar, S. A.   +5 more
core   +1 more source

Application of Graph Spatio-Temporal Convolutional Neural Network in Motor Intention Recognition of Stroke Patients

康复学报
ObjectiveTo evaluate the decoding accuracy and model performance of a graph spatio-temporal convolutional neural network (G-STCNN) in motor intention recognition of stroke patients.MethodsWe developed a novel G-STCNN model by integrating graph ...
XU Hui, MA Jun, ZHANG Jingjing, ZHANG Tao, ZHAO Zhiwei, SHAN Chunlei   +5 more
doaj  

Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting

, 2020
Modeling complex spatial and temporal correlations in the correlated time series data is indispensable for understanding the traffic dynamics and predicting the future status of an evolving traffic system.
Bai, Lei, Wang, Can, Yao, Lina, Wang, Xianzhi, Li, Can   +4 more
core  

Optimizing Convolutional Neural Network Architectures

Mathematics
Convolutional neural networks (CNNs) are commonly employed for demanding applications, such as speech recognition, natural language processing, and computer vision.
Luis Balderas, Miguel Lastra, José M. Benítez   +2 more
doaj   +1 more source