The proceedings contain 13 papers. The special focus in this conference is on Learning, Evolution and Human Interaction. The topics include: Towards real-time behavioral evolution in video games;simulated road followi...
ISBN:
(纸本)9783319180830
The proceedings contain 13 papers. The special focus in this conference is on Learning, Evolution and Human Interaction. The topics include: Towards real-time behavioral evolution in video games;simulated road following using neuroevolution;enhancing active vision system categorization capability through uniform local binary patterns;learning in networked interactions;human robot-team interaction;an exploration on intuitive interfaces for robot control based on self organisation;adaptive training for aggression de-escalation;mobile GPGPU acceleration of embodied robot simulation;ashby’s mobile homeostat and multi-robot coverage.
Skin Cancer is life-threatening when diagnosed at a later stage. Early detection of skin cancers such as melanoma indicates a higher survival rate for the patient. Non-computer aided tools were used in the past such a...
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ISBN:
(纸本)9781728165417
Skin Cancer is life-threatening when diagnosed at a later stage. Early detection of skin cancers such as melanoma indicates a higher survival rate for the patient. Non-computer aided tools were used in the past such as the visual inspection using tools like the dermoscopy. Commercial tools were later introduced that allowed the examiners to examine the images obtained from the dermoscopy using techniques such as the ABCD rule and 7-point checklist. Deep Learning has proven to be the state-of-the-art for computervision problems such as image classification. A lot of research has been carried out in the application of deep learning for automating skin cancer screening. This paper presents an analysis of the existing work carried out in the area of automatic skin cancer screening and the different steps involved in building a skin cancer classification tool for skin cancer screening. The limitations of the various existing approaches are explored, and the results of the analysis will be used as part of an ongoing research to design and develop a robust system that will address the identified cons.
When used for tracking, the combination of infrared (IR) and an internal measurement unit (IMU) allows researchers and industry to locate objects to within 1 cm at over 200 Hz with a latency less than 2 ms. This novel...
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The proceedings contain 81 papers. The topics discussed include: adaptive central pattern generators to control human/robot interactions;modelling personality prediction from user's posting on social media;web bas...
ISBN:
(纸本)9781728133331
The proceedings contain 81 papers. The topics discussed include: adaptive central pattern generators to control human/robot interactions;modelling personality prediction from user's posting on social media;web based application for ordering food raw materials;comparison of Gaussian hidden Markov model and convolutional neural network in sign language recognition system;intelligent computational model for early heart disease prediction using logistic regression and stochastic gradient descent (a preliminary study);an efficient system to collect data for ai training on multi-category object counting task;a comparison of artificial intelligence-based methods in traffic prediction;impact of computervision with deep learning approach in medical imaging diagnosis;and development of portable temperature and air quality detector for preventing COVID-19.
In this paper, we are mostly interested in investigating how the study and discovery of the human visual cortex could be utilised to improve the computational models for visual recognition by computervision. Many of ...
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ISBN:
(纸本)9781479986880
In this paper, we are mostly interested in investigating how the study and discovery of the human visual cortex could be utilised to improve the computational models for visual recognition by computervision. Many of the brain perceptual abilities in vision have corresponding algorithms exist in computervision, and in this paper we discuss three such models. First we present a model that has the ability for iterative bottom-up/top-down recognition, and experimental results on applying the model for facial landmark detection has shown improved accuracy over benchmark approaches. Second we introduce a new SOM model that could be deep and invariant, which could achieve significantly improved digit recognition accuracy over traditional SOM. And third we show how the convolutional neural network could be combined with linear coding based architecture, where experimental results show that the proposed model could outperform many existing algorithms for image classification.
The paper focuses on the problem of structure from motion and proposes a spatial-and-temporal-weighted factorization algorithm. The contributions of the paper are as follows: First, it is demonstrated that the image r...
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In this paper, an efficient concealed weapon detection algorithm is proposed which uses the characteristics of human visual system in frame let domain. The main idea is to decompose the visual and IR/MMW images to be ...
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This paper presents a new industrial robot control system integrated with real-time image processing based on a Windows PC. This enables both machine vision and robot control tasks to be carried out on a single genera...
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ISBN:
(纸本)9781538676752
This paper presents a new industrial robot control system integrated with real-time image processing based on a Windows PC. This enables both machine vision and robot control tasks to be carried out on a single general-purpose computer rather than using two separate systems to perform different tasks. To accomplish this, a three-layer software structure is developed along with a series of standard peripheral devices in the hardware layout. Real-time performance of the system is tested and we demonstrate the system on a DELTA parallel manipulator. Experimental results show that the manipulator can pick up 120 objects on a moving conveyor per minute. This work demonstrates the feasibility of integrating real-time machine vision tasks with robot control tasks without dedicated hardware.
robotics has undoubtedly found its way deeper into every day human tasks up to the point where now they even share workspaces with people. In this context, social robotics has increased its field of action, one import...
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ISBN:
(纸本)9783030425203;9783030425197
robotics has undoubtedly found its way deeper into every day human tasks up to the point where now they even share workspaces with people. In this context, social robotics has increased its field of action, one important part is the advances in aspects that make up the Human-Machine Interaction. This article reports the advance that an investigation team at Universidad de las Fuerzas Armadas ESPE has done to create a test platform for computervision algorithms. This approach consists of a 3-DOF articulated robotic head with anthropomorphic characteristics, considering the guidelines established by different authors for social robotics, besides it provides affordable, flexible and scalable hardware resources to facilitate the implementation, testing, analysis and development of different stereo artificial vision algorithms. The system, called Visart, is intended to work in more natural situations than independent cameras, therefore, work deeply in Human-robot Interaction. As the first report of the Visart prototype, some basic tests with the platform were performed, they consist of face detection, facial and expression recognition, object tracking, and object distance calculation. The results obtained were consistent, opening a door for further research focusing on the comparison of more computervision algorithms to examine their performance in real scenarios and evaluate them more naturally with our prototype for Human-robot Interaction.
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