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A Critical Analysis of computer Aided Approaches for Skin Cancer Screening 1

A Critical Analysis of Computer Aided Approaches for Skin Ca...

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1st International conference on Image Processing and robotics (ICIP)

作者： Selvarasa, Minoj Aponso, Achala Informat Inst Technol Colombo 6 Sri Lanka

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 computer vision 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.

关键词： Skin Cancer Screening computer vision Deep Learning Augmentation Segmentation CNN

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Construction of a computer vision Test Platform: VISART for Facial Recognition in Social robotics 1st

Construction of a Computer Vision Test Platform: VISART for ...

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1st International conference on Applied Technologies (ICAT)

作者： Rodriguez, Edwin Gutierrez, Christian Ochoa, Cristian Travez, Freddy Escobar, Luis Loza, David Univ Fuerzas Armadas ESPE Dept Energy & Mech Sangolqui 170121 Pichincha Ecuador

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 computer vision 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 computer vision algorithms to examine their performance in real scenarios and evaluate them more naturally with our prototype for Human-robot Interaction.

关键词： HRI computer vision Human-robot Interaction Anthropomorphic robot Social robotics

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Human operator cognitive availability aware Mixed-Initiative control 1

Human operator cognitive availability aware Mixed-Initiative...

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1st IEEE International conference on Human-Machine Systems (ICHMS)

作者： Petousakis, Giannis Chiou, Manolis Nikolaou, Grigoris stolkin, Rustam Univ West Attica Egaleo Greece Univ Birmingham Extreme Robot Lab ERL Birmingham W Midlands England Univ Birmingham Natl Ctr Nucl Robot NCNR Birmingham W Midlands England

ISBN: (纸本)9781728158716

This paper presents a Cognitive Availability Aware Mixed-Initiative Controller for remotely operated mobile robots. The controller enables dynamic switching between different levels of autonomy (LOA), initiated by either the AI and/or the human operator. The controller leverages a state-of-the-art computer vision method and an off-the-shelf web camera to infer the cognitive availability of the operator and inform the AI-initiated LOA switching. This constitutes a qualitative advancement over previous Mixed-Initiative (MI) controllers. The controller is evaluated in a disaster response experiment, in which human operators have to conduct an exploration task with a remote robot. MI systems are shown to effectively assist the operators, as demonstrated by quantitative and qualitative results in performance and workload. Additionally, some insights into the experimental difficulties of evaluating complex MI controllers are presented.

关键词： Controllers

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Object Detection and Classification Using Machine Learning Techniques: A Comparison of Haar Cascades and Neural Networks 1

Object Detection and Classification Using Machine Learning T...

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1st International conference on Data Science, Machine Learning and Artificial Intelligence, DSMLAI 2021

作者： Mukabe, Chisulo Suresh, Nalina Hashiyana, Valerians Haiduwa, Titus Sverdlik, William School of Computing University of Namibia Windhoek Khomas Namibia Computer Department Eastern Michigan University Ypsilanti MI United States

ISBN: (纸本)9781450387637

Object recognition and object detection are sub fields of computer vision, the task of giving computers the ability to perceive and respond to the world around them. This is a very useful technology and has many different applications in many different disciplines. Examples of applications include but are not limited to: Use in security by using facial recognition;use in the medical field for classification of cancer types (malignant or benign) or detecting sickle cells in the blood;or it can be used as a research tool to automatically record data (e.g. count the number of trucks that use a particular highway);or used in agriculture or industrialization for quality control;or for entertainment purposes in games that can detect and track a users' movement to control a character in a game. And there are many more examples, in which it can be used. However, just as they are many applications, there are also many methods of implementing these systems, such as Convolutional neural networks, Haar cascades, Scale-Invariant Feature Transformations (SIFT), Histogram of Oriented Gradients (HOG) and several others including combinations of these. Each technique may have different setup procedures and different applications where one may work better than the other. This paper aims to measure and give a comparison of some of these techniques for object detection and tracking, by looking at their training and testing time as well as accuracy. The methods used in this paper was Haar Cascades and Neural Networks. The purpose of this paper is to learn more about these machine learning techniques by comparing the way they work and the way they were implemented, by doing so one can also understand contexts in which to use these systems. The artifacts used in this paper included a robot that can track an object and an application that could classify an image based on a set of objects it was trained on, that is the application can determine what the picture is of based on a set of image

关键词： Quality control

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Exploring a Ground-Air Personal Space in Human-Drone Interactions 1

Exploring a Ground-Air Personal Space in Human-Drone Interac...

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1st International conference on Image Processing and robotics (ICIP)

作者： Ariyasena, Erangi P. Manawadu, Udaka A. Abeyratne, Kasun R. De Silva, P. Ravindra S. Univ Sri Jayewardenepura Ctr Robot & Intelligent Syst Dept Comp Sci Fac Appl Sci Nugegoda Sri Lanka Univ Aizu Grad Sch Comp Sci & Engn Robot Engn Lab Aizu Wakamatsu Fukushima Japan

ISBN: (纸本)9781728165417

Drones are becoming more popular among emerging technologies and expected to be ubiquitous soon. Even though drones were used only in the military domain in earlier decades, with the recent advancements of UAV (Unmanned Aerial Vehicles) technology, drones have started to appear in civil domain in a rapid manner. But until now, less work has been considered drone as a social entity. In order for drones to approach humans, the acceptance level of the drone as a social entity and the proxemics ranges for a comfortable interaction need to be better understood. So in this paper we are presenting an autonomous drone application which can effectively identify the efficient parameters of Human Drone Interactive space and continuously maintain those parameters as a companion was studied. Thereby trying to understand the convenient proxemics boundaries in Human Drone interactions. The results have shown that acceptance level of the drone as a companion is high among the participants and 1.75m-3.4m is the horizontal distance range and 1.9m-3m is the altitude range that the users preferred most to interact with a companion drone.

关键词： Human Drone Interaction Human robot Interaction Autonomy computer vision Companionship Proxemics

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An Abstraction of Semantic Segmentation Algorithms 1

An Abstraction of Semantic Segmentation Algorithms

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1st International conference on Machine vision and Image Processing, MVIP 2020

作者： Teymoori, Reihaneh Nabizadeh, Zahra Karimi, Nader Samavi, Shadrokh Isfahan University of Technology Department of Electrical and Computer Engineering Isfahan84156-83111 Iran

ISBN: (纸本)9781728168326

semantic segmentation is a process of classifying each pixel in the image. Due to its advantages, semantic segmentation is used in many tasks like cancer detection, robot-assisted surgery, satellite images, self-driving car, etc. in this process, accuracy and efficiency are the two crucial goals for this purpose, there are several state-of-the-art neural networks. In each method, by employing different techniques, new solutions have been presented for increasing efficiency, accuracy, and saving the costs. The diversity of the implemented approaches for semantic segmentation makes it difficult for researchers to achieve a comprehensive view. Due to this, in this paper, an abstract framework for semantic segmentation is offered. This framework consists of 4 blocks that cover the majority of the methods that have been proposed for semantic segmentation. In this paper, we also attempt to compare different approaches and consider the importance of each part in semantic segmentation. Although our proposed framework considers most of the previous methods, maybe a few papers need new blocks. © 2020 IEEE.

关键词： Semantic Segmentation

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robot Eye: Automatic Object Detection and Recognition Using Deep Attention Network to Assist Blind People 1

Robot Eye: Automatic Object Detection and Recognition Using ...

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1st International conference on Pervasive Artificial Intelligence, ICPAI 2020

作者： Yohannes, Ervin Lin, Paul Lin, Chih-Yang Shih, Timothy K. National Central University Department of Computer Science and Information Engineering Taoyuan Taiwan Yuan-Ze University Department of Electrical and Engineering Taoyuan Taiwan

ISBN: (纸本)9781665404839

Detection and Recognition is a well-known topic in computer vision that still faces many unresolved issues. One of the main contributions of this research is a method to guide blind people around an outdoor environment with the assistance of a ZED stereo camera, a camera that can calculate depth information. In this paper, we propose a deep attention network to automatically detect and recognize objects. The objects are not only limited to general people or cars, but include convenience stores and traffic lights as well, in order to help blind people cross a road and make purchases in a store. Since public datasets are limited, we also create a novel dataset with images captured by the ZED stereo camera and collected from Google street View. When testing with images of different resolutions, our method achieves an accuracy rate of about 81%, which is better than naive YOLO v3. © 2020 IEEE.

关键词： stereo image processing

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robot teaching assistant and physical programming class for programming education of young children 20

Robot teaching assistant and physical programming class for ...

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Proceedings of the 2020 1st International conference on Control, robotics and Intelligent System

作者： Xianyu Qi Wei Wang Ziwei Liao Xiaoyu Zhang Lin Xue Xu Zhang Jing Li Tong Fang Ran Wei Beihang University China Beijing Evolver Robotics Technology Co. Ltd China The High School Affiliated to Renmin University of China China Fengtai School of the High School Affiliated to Renmin University of China China

ISBN: (纸本)9781450388054

This paper proposes a programming class for young children. In order to reduce the burden on teachers and attract students' interest, a robot teaching assistant is used to explain programming knowledge, verify and run programs. Different from writing programs on a computer, the physical board programming is employed to develop logical thinking of young children and prevent them from the vision harm of facing computer screens for a long time and the lack of reality from immersion in the virtual world. Based on the knowledge points of programming, we have designed a course with 16 lessons. The course has been successfully applied in many kindergartens and elementary schools. We use the questionnaires for students and teachers to evaluate the course and the experimental results show that it is effective.

关键词： Programming education robot teaching assistant Physical programming

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1st International Workshop on Active Inference, IWAI 2020 held in conjunction with the European conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2020

1st International Workshop on Active Inference, IWAI 2020 he...

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1st International Workshop on Active Inference, IWAI 2020 held in conjunction with the European conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2020

ISBN: (纸本)9783030649180

The proceedings contain 19 papers. The special focus in this conference is on . The topics include: You only look as much as you have to: Using the free energy principle for active vision;modulation of viability signals for self-regulatory control;end-effect exploration drive for effective motor learning;learning where to park;integrated world modeling theory (iwmt) implemented: Towards reverse engineering consciousness with the free energy principle and active inference;confirmatory evidence that healthy individuals can adaptively adjust prior expectations and interoceptive precision estimates;visual search as active inference;sophisticated affective inference: Simulating anticipatory affective dynamics of imagining future events;causal blankets: Theory and algorithmic framework;active inference or control as inference? a unifying view;active inference for fault tolerant control of robot manipulators with sensory faults;a worked example of fokker-planck-based active inference;dynamics of a bayesian hyperparameter in a markov chain;online system identification in a duffing oscillator by free energy minimisation;hierarchical gaussian filtering of sufficient statistic time series for active inference;deep active inference for partially observable mdps;sleep: Model reduction in deep active inference.

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Recognition of Dandelion Weed via computer vision for a Weed Removal robot 1

Recognition of Dandelion Weed via Computer Vision for a Weed...

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1st International conference on Industrial Artificial Intelligence (IAI)

作者： Babiker, Ibrahim Xie, Wen-Fang Chen, Guangyi Concordia Univ Dept Mech Ind & Aerosp Engn Montreal PQ Canada

ISBN: (纸本)9781728135939

This paper introduces novel methods for distinguishing dandelion weed leaves from grass blades and identifying the centroids of dandelion weeds by means of a webcam. Firstly, a method of isolating the colour green using a Hue-Saturation-Value (HSV) scheme is proposed. Next, a technique for filtering the high frequency grass blades is developed to isolate individual low frequency of weed leaves. Subsequently, two novel methods: the lengthwise intersection method and mean centroid method are proposed to detect the location of the weed center based on the individual weed leaves. The detected location of the dandelion weed centroid has been used as the desired destination of autonomous driving system of a weed removal robot for successful dandelion removal.

关键词： Image color analysis Blades computer vision Thresholding (Imaging) Feature extraction

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