“…The final goal being the development of a low-cost system, we studied several architectures of convolutional neural networks (CNN) and showed that a more complex architecture does not necessarily lead to better results. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso

“…For the optical flow algorithms, the convolutional neural network (CNN)-based models as well as the original schemes like the Lucas-Kanade and Farnebäck methods are considered. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso

“…In this paper, we propose a novel bilinear convolutional neural network- (Bilinear-CNN-) based model with a bilinear convolutional module and a soft attention module to tackle this problem. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso

“…In many detection tasks ranging from semantic segmentation of medical images to time-series data classification, multireceptive field CNN has improved performance. Notably, the nature of the ECG dataset made performance improvement possible by using a multireceptive field CNN (MRF-CNN). …”
Enlace del recurso
Enlace del recurso
Enlace del recurso

Enlace del recurso
Enlace del recurso
Enlace del recurso

“…Using a convolutional neural network (CNN) to extract the features of Chinese painting, the image features of Chinese painting are extracted by fine-tuning the pretrained VGG-F model. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso

“…If a fault occurs, it will cause serious damage to the entire equipment and can even have a major impact on the entire production process, leading to a serious economic and social life. In this paper, a CNN-based machine learning fault diagnosis method is proposed to address the problem of high incidence of motor faults and difficulty in identifying fault types. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso

“…To solve these problems, this paper proposes a T-CNN time series classification method based on a Gram matrix. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso

“…The results show that the method based on MsCNN–BiLSTM can effectively identify the aeroengine working conditions including transition conditions accurately.…”
Enlace del recurso
Enlace del recurso
Enlace del recurso

“…The model was developed based on localization for the region of interest (ROI) using a mask region-based convolutional neural networks R-CNN and a classification network for the presence of PPA using CNN deep learning algorithms. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso

“…The aim of this paper is to propose an image detector embedding a resource constrained convolutional neural network (CNN) implemented in a low cost, low power platform, named OpenMV Cam H7 Plus, to perform a real-time classification of plant disease. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso

“…Keeping this research gap and hindrance faced by the previous researchers the present study aims to fulfill the requirements, the efforts can be made to overcome this problem, and the proposed automated CNN-LSTM with ResNet-152 algorithm. Compared with the existing techniques, the proposed techniques achieved a higher level of accuracy of 98% by applying the hybrid deep learning algorithm.…”
Enlace del recurso
Enlace del recurso
Enlace del recurso

“…In this work, a novel hybrid model is proposed by combining the transformer with a convolution neural network (CNN). Compared to traditional ViTs and CNNs, the proposed model achieves state-of-the-art performance when trained on small EM datasets. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso

“…After such two-fold data expansion, a balanced data set is obtained and imported to an improved 2dCNN based on the LeNet-5 to implement fault diagnosis. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso

Enlace del recurso
Enlace del recurso
Enlace del recurso

“…In this study, we propose a novel convolutional neural networks (CNN) architecture to detect ECG types. In addition, the proposed CNN can automatically extract features from images. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso

“…The first generator comprises a U-net network, while the second utilizes a mask R-CNN. The task of lung segmentation involves a two-class classification of the pixels in each image, categorizing lung pixels in one class and the rest in the other. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso

“…Meanwhile, optimizing the highly defined number of convolutional neural network (CNN) hyperparameters (hundreds to thousands) is a useful direction to improve its overall performance and overcome its cons. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso

“…Based on the annotated recordings, we developed and compared two BS recognition models: CNN and LSTM. Our CNN model could detect BSs with an accuracy of 88.9% andan F measure of 72.3% using cross evaluation, thus displaying better performance than the LSTM model (82.4% accuracy and 65.8% F measure using cross validation). …”
Enlace del recurso
Enlace del recurso
Enlace del recurso

“…To explore the potential relationship between the leading vehicle and the following vehicle during car-following, we proposed a novel car-following model combining a convolutional neural network (CNN) with a long short-term memory (LSTM) network. …”
Enlace del recurso
Enlace del recurso
Enlace del recurso