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Running Tasks on a Scheduled Basis Using the Azure "Logic Apps" Service

Azure Logic Apps is an interesting cloud service that provides you with features to schedule and/or automate tasks, business processes, and workflows when you need to integrate data and services across enterprises or organizations.
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Deep Learning – Semantic Segmentation

Today, semantic segmentation is one of the key problems in the field of computer vision. Looking at the big picture, semantic segmentation is one of the high-level tasks that paves the way for a holistic understanding of the scene. The importance of understanding the scene as a fundamental problem with computer vision is highlighted by the fact that an increasing number of applications stem from the acquisition of knowledge from images.
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Jenkins Pipelines, or Five Instructions Yielding Utility

When we started the internal project that will be announced soon, there were many decisions we had to make regarding architecture, infrastructure, and development processes. Naturally, we pooled our knowledge and experience together, taking what worked best for us in the past and balancing it with the industry's contemporary best practices. One such decision was to use […]
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TDD vs. BDD vs. ATDD

Sometimes, software development can be overwhelming. There are lots of languages, frameworks, and tools to know about. Also, there are processes to follow. For a developer, in most cases, it’s not the work of writing out code that’s difficult. The complexity comes in determining what kind of code to write, how to handle different cases, […]
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IBM ACE Flow Testing, Debugging and Troubleshooting

The flow execution process inside the IBM App Connect Enterprise (ACE) integration node consists of at least three steps or nodes. Do not confuse flow nodes with integration nodes. An integration node represents a group of IBM ACE applications inside the integration server, while a flow node stands for the unit of work inside the […]
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Appian – Low-Code Platform

Appian is an intelligent business process management (iBPM) and automation system. Its goal is to help you turn great ideas into powerful business applications that deliver significant value. In this post, we will discuss Appian building blocks and their application in creating a business application. Process Model The process model is the most important Appian […]
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Deep Learning - Object Detection

In the last article series written by my colleague, we learned image classification and its implementation. Now we are going to take a glance at the science of object detection. Whereas image classification returns a class and probability for the whole image, object detection finds a list of objects on the image and returns it for […]
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Spatial Data in .NET

Spatial data contains information about geometrical properties of a certain entity, such as the position, length and surface area. This kind of data could theoretically also be stored using conventional data types, but it would be quite inconvenient for processing. Therefore, many database systems and software frameworks support using special datatypes for spatial data. In this post handling spatial data in the .NET Framework will be covered.
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Deep Learning Neural Networks – PART TWO

Based on convolutional neural network architecture, which we explained in part one of this article series, we will show you how to create a simple deep learning convolutional neural network for image classification for the CIFAR-10 dataset.
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Deep Learning Neural Networks – PART ONE

The most well-known deep learning architectures are certainly deep neural networks, DBF (deep belief network), and recurrent neural networks. Some of the fields where deep learning can be applied are computer vision, speech recognition, sound recognition, social filtering network, bioinformatics, drug design, advanced image processing, segmentation, whatever data has a time component, etc. In many scenarios, deep learning has shown equal and even superior results in relation to human expertise.
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Projekt je sufinancirala Europska unija iz Europskog fonda za regionalni razvoj. Sadržaj emitiranog materijala isključiva je odgovornost tvrtke Serengeti d.o.o.