Endoscopic image analysis using Deep Convolutional GAN and traditional data

One big challenge encountered in the medical field is the availability of only limited annotated datasets for research. On the other hand, medical image annotation requires a lot of input from medical experts. It is noticed that machine learning and deep learning are producing better results in the area of image classification. However, these techniques require large training datasets, which is the major concern for medical image processing. Another issue is the unbalanced nature of the different classes of data, leading to the under-representation of some classes. Data augmentation has emerged as a good technique to deal with these challenges. In this work, we have applied traditional data augmentation and Generative Adversarial Network (GAN) on endoscopic esophagus images to increase the number of images for the training datasets. Eventually we have applied two deep learning models namely ResNet50 and VGG16 to extract and represent the relevant cancer features. The results show that the accuracy of the model increases with data augmentation and GAN. In fact, GAN has achieved the highest accuracy, that is, 94% over non-augmented training set and traditional data augmentation for VGG16

Participatory Design with Blind Users: A Scenario-based Approach

Abstract. Through out the design process, designers have to consider the needs of potential users. This is particularly important, but rather harder, when the designers interact with the artefact to-be-designed using different senses or devices than the users, for example, when sighted designers are designing an artefact for use by blind users. In such cases, designers have to ensure that the methods used to engage users in the design process and to communicate design ideas are accessible. In this paper, we describe a participatory approach with blind users based on the use of a scenario and the use of dialogue-simulated interaction during the development of a search interface. We achieved user engagement in two ways: firstly, we involved a blind user with knowledge of assistive technologies in the design team and secondly, we used a scenario as the basis of a dialogue between the designers and blind users to simulate interaction with the proposed search interface. Through this approach, we were able to verify requirements for the proposed search interface and blind searchers were able to provide formative feedback, to critique design plans and to propose new design ideas based on their experience and expertise with assistive technologies. In this paper, we describe the proposed scenario-based approach and examine the types of feedback gathered from its evaluation with blind users. We also critically reflect on the benefits and limitations of the approach, and discuss practical considerations in its application

An ICT architecture for Smart Local Councils: a Mauritian case study

The purpose of this paper is to present the work done with regards to the development of an ICT architecture for Smart Local Councils in Mauritius (SLCs). This is in line with vision of the Mauritian government to convert the Mauritius into a Smart Island. Local councils play an important role in the delivery of services to citizen and their conversion to Smart Local Councils will contribute to the transformation of the island. The methodology used to develop the ICT architecture is presented. The components for each layer, based on architecture principles are discussed. The validation which include, validation against the architecture principles, validation through stakeholders’ focus groups and also validation in terms of its contribution to smartness are discussed. This paper provides added value as it shows how the gaps for converting Mauritian local councils into SLCs can be addressed through the proposed architecture. It provides the main building blocks which can aid in designing the roadmap for ICT architecture for Mauritian SLCs

Implementace Datových skladů ve firmě VAKUS, s.r.o. Vítkov

Import 20/04/2006Prezenční výpůjčkaVŠB - Technická univerzita Ostrava. Ekonomická fakulta. Katedra (155) informatiky v ekonomic