A survey on deep learning for data-driven soft sensors
Q Sun, Z Ge - IEEE Transactions on Industrial Informatics, 2021 - ieeexplore.ieee.org
Soft sensors are widely constructed in process industry to realize process monitoring, quality
prediction, and many other important applications. With the development of hardware and …
prediction, and many other important applications. With the development of hardware and …
CNN architectures for geometric transformation-invariant feature representation in computer vision: a review
A Mumuni, F Mumuni - SN Computer Science, 2021 - Springer
One of the main challenges in machine vision relates to the problem of obtaining robust
representation of visual features that remain unaffected by geometric transformations. This …
representation of visual features that remain unaffected by geometric transformations. This …
Deep learning-based applications for safety management in the AEC industry: A review
Safety is an essential topic to the architecture, engineering and construction (AEC) industry.
However, traditional methods for structural health monitoring (SHM) and jobsite safety …
However, traditional methods for structural health monitoring (SHM) and jobsite safety …
Crop pest recognition in natural scenes using convolutional neural networks
Crop diseases and insect pests are major agricultural problems worldwide, because the
severity and extent of their occurrence causes significant crop losses. In addition, traditional …
severity and extent of their occurrence causes significant crop losses. In addition, traditional …
A novel deep learning method for intelligent fault diagnosis of rotating machinery based on improved CNN-SVM and multichannel data fusion
Intelligent fault diagnosis methods based on deep learning becomes a research hotspot in
the fault diagnosis field. Automatically and accurately identifying the incipient micro-fault of …
the fault diagnosis field. Automatically and accurately identifying the incipient micro-fault of …
Detection of strawberry diseases using a convolutional neural network
The strawberry (Fragaria× ananassa Duch.) is a high-value crop with an annual cultivated
area of~ 500 ha in Taiwan. Over 90% of strawberry cultivation is in Miaoli County …
area of~ 500 ha in Taiwan. Over 90% of strawberry cultivation is in Miaoli County …
A novel scene classification model combining ResNet based transfer learning and data augmentation with a filter
S Liu, G Tian, Y Xu - Neurocomputing, 2019 - Elsevier
Scene classification is a significant aspect of computer vision. Convolutional neural
networks (CNNs), a development of deep learning, are a well-understood tool for image …
networks (CNNs), a development of deep learning, are a well-understood tool for image …
Pineapple (Ananas comosus) fruit detection and localization in natural environment based on binocular stereo vision and improved YOLOv3 model
TH Liu, XN Nie, JM Wu, D Zhang, W Liu, YF Cheng… - Precision …, 2023 - Springer
The detection and localization of pineapple fruit must be successfully conducted to realize
intelligent picking. This paper proposed a method for detecting and localizing pineapples in …
intelligent picking. This paper proposed a method for detecting and localizing pineapples in …
A data-driven-based fault diagnosis approach for electrical power DC-DC inverter by using modified convolutional neural network with global average pooling and 2 …
W Gong, H Chen, Z Zhang, M Zhang, H Gao - Ieee Access, 2020 - ieeexplore.ieee.org
A novel convolutional neural network namely the modified CNN-GAP model is proposed for
fast fault diagnosis of the DC-DC inverter. This method improves the model structure of the …
fast fault diagnosis of the DC-DC inverter. This method improves the model structure of the …
Towards robust CNN-based object detection through augmentation with synthetic rain variations
G Volk, S Müller, A Von Bernuth… - 2019 IEEE intelligent …, 2019 - ieeexplore.ieee.org
Convolutional Neural Networks (CNNs) achieve high accuracy in vision-based object
detection tasks. For their usage in the automotive domain, CNNs have to be robust against …
detection tasks. For their usage in the automotive domain, CNNs have to be robust against …