Results 51 to 60 of about 6,849,681 (296)
Improved Urdu-English Neural Machine Translation with a fully Convolutional Neural Network Encoder [PDF]
International Journal of Mathematical, Engineering and Management SciencesNeural machine translation (NMT) approaches driven by artificial intelligence (AI) has gained more and more attention in recent years, mainly due to their simplicity yet state-of-the-art performance.
Huma Israr +2 more
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Fully convolutional neural networks for remote sensing image classification [PDF]
2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016 We propose a convolutional neural network (CNN) model for remote sensing image classification. Using CNNs provides us with a means of learning contextual features for large-scale image labeling. Our network consists of four stacked convolutional layers that downsample the image and extract relevant features.
Maggiori, Emmanuel +3 more
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Chainsaw: protein domain segmentation with fully convolutional neural networks
Bioinformatics, 2023 ABSTRACT 0.1 Motivation Protein domains are fundamental units of protein structure and play a pivotal role in understanding folding, function, evolution, and design. The advent of accurate structure prediction techniques has resulted in an influx of new structural data, making the ...
Jude Wells +5 more
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IEEE Access, 2020 Unconventional reservoir classification suffers low accuracy because of the complex geophysical properties. With good performance and moderate cost, geophysical logging is considered to be of great potential as the compromise solution between seismic and
Kai Zhu +4 more
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SF-ICNN: Spectral–Fractal Iterative Convolutional Neural Network for Classification of Hyperspectral Images [PDF]
One primary concern in the field of remote-sensing image processing is the precise classification of hyperspectral images (HSIs). Lately, deep-learning models have demonstrated cutting-edge results in HSI classification.
Akbari, Vahid +5 more
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Sensor and Actuator Fault Diagnosis for Robot Joint Based on Deep CNN
Entropy, 2021 This paper proposes a data-driven method-based fault diagnosis method using the deep convolutional neural network (DCNN). The DCNN is used to deal with sensor and actuator faults of robot joints, such as gain error, offset error, and malfunction for both
Jinghui Pan, Lili Qu, Kaixiang Peng
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Deep Convolutional Generalized Classifier Neural Network
, 2020 WOS: 000521878300002Up to date technological implementations of deep convolutional neural networks are at the forefront of many issues, such as autonomous device control, effective image and pattern recognition solutions.
Sarıgül, Mehmet +2 more
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Fully convolutional network based ship plate recognition [PDF]
, 2018 Ship plate recognition is challenging due to variations of plate locations and text types. This paper proposes an effcient Fully Convolutional Network based Plate Recognition approach FCNPR, which uses a CNN (Convolutional Neural Network) to locate ships,
Liu, X. (Xin) +17 more
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LIDAR-Camera Fusion for Road Detection Using Fully Convolutional Neural Networks
, 2019 In this work, a deep learning approach has been developed to carry out road detection by fusing LIDAR point clouds and camera images. An unstructured and sparse point cloud is first projected onto the camera image plane and then upsampled to obtain a set
Svensson, Lennart +7 more
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Transitioning Between Convolutional and Fully Connected Layers in Neural Networks [PDF]
, 2017 Digital pathology has advanced substantially over the last decade however tumor localization continues to be a challenging problem due to highly complex patterns and textures in the underlying tissue bed. The use of convolutional neural networks (CNNs) to analyze such complex images has been well adopted in digital pathology.
Shazia Akbar +4 more
openaire +4 more sources