The paper presents a solution for visual servoing problem that is implemented on a robotic arm from an industrial flexible assembly line. This line respects the Industry 4.0 paradigm, thus having a modular structure c...
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ISBN:
(数字)9781728157429
ISBN:
(纸本)9781728157436
The paper presents a solution for visual servoing problem that is implemented on a robotic arm from an industrial flexible assembly line. This line respects the Industry 4.0 paradigm, thus having a modular structure consisting of five stations. Each station includes a Programmable Logic controller equipment for local control and communication modules for connection with other stations. The paper is focused on the design and implementation of the visual servoing system which ensures the line flexibility. The experimental results validate the system functionality and indicate significant performances.
In this paper we present a simple and efficient approach based on the decision fusion of the characteristics-based method (ABCD) and deep neural networks-based method to classify skin lesions as melanoma or common nev...
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ISBN:
(数字)9781665404990
ISBN:
(纸本)9781665405003
In this paper we present a simple and efficient approach based on the decision fusion of the characteristics-based method (ABCD) and deep neural networks-based method to classify skin lesions as melanoma or common nevus. As deep neural networks AlexNet and GoogLeNet were used. The decision fusion considers a convolutional rule of associated weights and probabilities provided by the previous classifiers. The method was implemented in the Matlab software and dermoscopic images from the PH2 and ISIC databases were used. The experimental results and the melanoma detection rate validate the proposed approach.
Nowadays, unmanned aerial vehicles (UAVs) and wireless sensor networks (WSNs) are often integrated in collaborative systems for data collection. In this paper, a specific UAV trajectory design for effective and secure...
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In this paper we aim to analyze the response of the target audience to out-of-home advertising panels mounted in display windows. We track people passing in front of the panels and, if they approach the panel, looking...
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ISBN:
(数字)9781728168432
ISBN:
(纸本)9781728168449
In this paper we aim to analyze the response of the target audience to out-of-home advertising panels mounted in display windows. We track people passing in front of the panels and, if they approach the panel, looking directly at it, we analyze their facial movements, to see whether the advert appeals to them or not. The approach is based on video data gathering using a static IP camera, storage and analysis, aiming to deliver real-time results. We use neural networks and support vector machines to determine facial microexpression. Results are correlated with information about the adverts displayed to be of use to advertising providers.
This paper is proposing a model predictive control (MPC) approach for a pantograph-catenary positioning system. A transfer function model is obtained from the state space model. Future algorithms will be applied on th...
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ISBN:
(数字)9781728198095
ISBN:
(纸本)9781728198101
This paper is proposing a model predictive control (MPC) approach for a pantograph-catenary positioning system. A transfer function model is obtained from the state space model. Future algorithms will be applied on the input/output form of the system. This model is discretized. Over the discretized model an MPC algorithm is applied using a model horizon of dimension 10. Simulations are showing the performances of the MPC controller applied on the nonlinear system for different input speed values of the train.
Integrating innovative technologies in terrestrial-satellite networks are needed to enable Unmanned Aerial Vehicles (UAV) application developers to achieve better results and optimize solutions. Managing a complex UAV...
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One of the most dangerous threats on the internet nowadays is phishing attacks. This type of attack can lead to data breaches, and with it to image and financial loss in a company. The most common technique to exploit...
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ISBN:
(数字)9780738112657
ISBN:
(纸本)9781665418850
One of the most dangerous threats on the internet nowadays is phishing attacks. This type of attack can lead to data breaches, and with it to image and financial loss in a company. The most common technique to exploit this type of attack is by sending emails to the target users to trick them to send their credentials to the attacker servers. If the user clicks on the link from the email, then good detection is needed to protect the user credentials. Many papers presented computer Vision as a good detection technique, but we will explain why this solution can generate lots of false positives in some important environments. This paper focuses on challenges of the computer Vision detection technique and proposes a combination of multiple techniques together with computer Vision technique in order to solve the challenges we have shown. We also will present a methodology to detect phishing attacks that will work with the proposed combination techniques.
A global characterization of the propagation behaviour that will allow a general approach of the Radio Frequency (RF) prediction is difficult to achieve. In this paper, based on field strength values collected in typi...
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The classification and segmentation of small region of interest from ground images is important in many domains: flood detection and evaluation, crop monitoring, environment monitoring, defense, etc. The paper uses a ...
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ISBN:
(数字)9781728198095
ISBN:
(纸本)9781728198101
The classification and segmentation of small region of interest from ground images is important in many domains: flood detection and evaluation, crop monitoring, environment monitoring, defense, etc. The paper uses a fusion scheme to classify small regions from remote images in four classes (different for satellite and unmanned aerial vehicle -UAVs). As novelty, two neural networks, considered as primary classifiers, AlexNet and Perceptron (the last based on ten textural image features) are combined in a convolutional scheme to make up the global classifier. The weights from the convolutional layer are calculated according to the performances of the primary classifiers in a validation phase. Two datasets with different images are used for classifier learning, validation, and testing, one consisting in images from satellite and another consisting in images from UAVs. The global system performances were better than those of the individual neural network (system components) accuracies.
When mining of input data is focused on rule induction, knowledge, discovered in exploration of existing patterns, is stored in combinations of certain conditions on attributes included in rule premises, leading to sp...
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When mining of input data is focused on rule induction, knowledge, discovered in exploration of existing patterns, is stored in combinations of certain conditions on attributes included in rule premises, leading to specific decisions. Through their properties, such as lengths, supports, cardinalities of rule sets, inferred rules characterise relations detected among variables. The paper presents research dedicated to analysis of these dependencies, considered in the context of various discretisation methods applied to the input data from stylometric domain. For induction of decision rules from data, Classical Rough Set Approach was employed. Next, based on rule properties, several factors were proposed and evaluated, reflecting characteristics of available condition attributes. They allowed to observe how variables and rule sets changed depending on applied discretisation algorithms.
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