Electronics | Free Full-Text | An Automated Recognition of
Nov 26, 2021 · The research used a convolutional neural network based on the Yolov3 and Yolov3 Tiny architecture. The choice of architectures based on Yolov3 was due to the fact that they ensured high efficiency in recognizing objects contained in …
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Static Hand Gesture Recognition Based on Convolutional
Dec 27, 2018 · This paper proposes a gesture recognition method using convolutional neural networks. The procedure involves the application of morphological filters, contour generation, polygonal approximation, and segmentation during preprocessing, in which they contribute to a better feature extraction. Training and testing are performed with different convolutional …
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Merging Subject Matter Expertise and Deep Convolutional
Based on the recent success of recurrent neural networks for time series domains, we propose a generic deep framework for activity recognition based on convolutional and LSTM recurrent units
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Implementation experiments on convolutional neural …
To facilitate the monitoring of excavator activities in a continuous and automated manner, this paper proposes a vision-based excavator pose estimation method. This pose estimation method calculates the relative position of the excavator elements, i.e., …
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Potential of Convolutional Neural Network-Based 2D Human
Jun 13, 2017 · To address these issues, the authors apply convolutional neural network (CNN) to human detection and pose estimation on sequential images from site conditions. Using the benchmark training datasets that do not include any images taken from the site, the result of 2D pose estimation in testing data shows that this approach achieves a high level
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Convolutional Neural Network Definition | DeepAI
A convolutional neural network, or CNN, is a deep learning neural network designed for processing structured arrays of data such as images. Convolutional neural networks are widely used in computer vision and have become the state of the art for many visual applications such as image classification, and have also found success in natural language processing for text …
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Potential of Convolutional Neural Network-Based 2D …
Jun 13, 2017 · To address these issues, the authors apply convolutional neural network (CNN) to human detection and pose estimation on sequential images from site conditions. Using the benchmark training datasets that do not include any images taken from the site, the result of 2D pose estimation in testing data shows that this approach achieves a high level of accuracy and …
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The Aircraft Pose Estimation Based on a Convolutional
Dec 19, 2019 · Inspired by human pose estimation, this paper presents an aircraft pose estimation method based on a convolutional neural network through reconstructing the two-dimensional skeleton of an aircraft. Firstly, the key points of an aircraft and the matching relationship are defined to design a 2D skeleton of an aircraft.
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International Journal of Advanced Robot visual measurement
Feb 01, 2021 · fast region based convolutional neural networks (RCNN),25 faster RCNN,26 and feature pyramid networks (FPNs).27 One-stage methods include YOLO,28 single-shot multibox detector,29 and RetinaNet.30 In different environments, different detection objects have different characteristics. Currently, scholars began
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Improving Preterm Infants' Joint Detection in Depth Images
Request PDF | Improving Preterm Infants' Joint Detection in Depth Images Via Dense Convolutional Neural Networks | Preterm infants' spontaneous motility is a valuable diagnostic and prognostic
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(PDF) 3D Human Activity Classification with 3D Zernike
3D Human Activity Classification with 3D Zernike Moment Based Convolutional, LSTM-Deep Neural Networks. 2021. Erdal Özbay. Download Download PDF. Full PDF Package Download Full PDF Package. This Paper. A short summary of this paper. 37 Full PDFs related to this paper. Read Paper. Download Download PDF.
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Convolutional Neural Network-Based Fish Posture Classification
Jun 21, 2021 · Meanwhile, a convolutional neural network is designed to classify the pose of the image. According to the above discussion, this study intends to solve a four-kind classification problem. It can also be seen as two binary classification problems: the first is to judge the head direction and second judges the orientation of belly.
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State of Health Estimation of Lithium-Ion Battery Using
The accurate state of health (SOH) estimation of lithium-ion batteries enables users to make wise replacement decision and reduce economic losses. SOH estimation accuracy is related to many factors, such as usage time, ambient temperature, charge and discharge rate, etc. Thus, proper extraction of features from the above factors becomes a great challenge.
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A New Convolutional Neural Network-Based System for NILM
Nov 02, 2020 · Electrical load planning and demand response programs are often based on the analysis of individual load-level measurements obtained from houses or buildings. The identification of individual appliances' power consumption is essential, since it allows improvements, which can reduce the appliances' power consumption. In this article, the …
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Vision-based excavator pose estimation using synthetically
The proposed method randomizes various critical features of the scene, such as excavator pose and texture, scene texture and lighting, camera location and field of view, and adds other elements, such as simulated dust and occluding objects, to the scene. A state-of-the-art deep convolutional neural network known as HRNet is adapted in this study.
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Dex-Net by BerkeleyAutomation
Dex-Net 2.0 is designed to generated training datasets to learn Grasp Quality Convolutional Neural Networks (GQ-CNN) models that predict the probability of success of candidate parallel-jaw grasps on objects from point clouds. GQ-CNNs may be useful for quickly planning grasps that can lift and transport a wide variety of objects a physical robot.
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Precise Measurement of Position and Attitude Based on
Aug 26, 2019 · In this paper, we propose an object pose measurement scheme based on convolutional neural network and we have successfully implemented end-to-end position and attitude detection. Furthermore, to effectively expand the measurement range and reduce the number of training samples, we demonstrated the independence of objects in each dimension …
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Precise Measurement of Position and Attitude Based on
In this paper, we propose an object pose measurement scheme based on convolutional neural network and we have successfully implemented end-to-end position and attitude detection.
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MobileNet Convolutional neural network Machine Learning
Jul 04, 2020 · MobileNets are small, low-latency, low-power models parameterized to meet the resource constraints of a variety of use cases. They can be built upon for classification, detection, embeddings, and
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Sep 06, 2012 · Precise Measurement of Position and Attitude Based on Convolutional Neural Network and Visual Correspondence Relationship IEEE Transactions on Neural Networks and Learning Systems, Vol. 31, No. 6 A Concise Guide to Feature Histograms with Applications to LIDAR-Based Spacecraft Relative Navigation
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