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In season two, we are back to explore practical applications of computer vision and their unique challenges. From identifying humans through facial analysis software to assisting doctors in diagnosing patients from medical images, computer vision is making a big impact across various domains. Join us as we unravel the mysteries of object detection, classification, and segmentation, and discover how these techniques are powering self-driving cars like Tesla's autopilot.
In the fifth episode we talk about Vision Transformer architectures. An approach for language translation and only recently applied to computer vision. This approach is more suitable for specific tasks as it takes context into account.
In the fourth episode we talk about the prevalent Deep Learning Architectures and their Building blocks. We cover how they work mathematically and how they are stacked together to achieve specific tasks.
In the third episode we dive deeper into Deep Learning and how Convolutional Neural Networks tackle Computer Vision tasks.
In the second episode we talk about the origin of Computer vision. Dating back to to a summer school in 1966. We also talk about classical approaches that are still used today as they excel at certain tasks like eye tracking.
In the first episode, we discuss the difference between artificial intelligence, machine learning, and deep learning, and explore the concept of artificial general intelligence. Tune in to learn more about the fascinating world of AI and machine learning!
In this last blog, we look at cutting-edge and future technologies that promise to solve UI Automation for user interfaces that are currently hard to test without a special setup.
In this blog, we will discuss the problems that come with selector-based approaches and how current tools try to remedy them with Smart Selectors and Self-healing Tests.
User Interface (UI) Automation is a hard task in todays world as the tools used are normally dependent on relying on structural clues instead of visual recognition of UI elements.In this three part blog series we will show where the current challenges of UI Automation are, what solutions to them exist and how AI/ML can help solve them in the future.
In recent years, the term smart selector has become established in UI testing. But what is it actually? This article explain what’s behind this term and whether they deliver what has been promised – namely, no more flaky tests. But before we get to smart selectors, we first need to understand what selectors actually are and what problems are associated with the classic approaches.
When writing tests, it is important to ensure that you are covering all of your code. This will help ensure that your tests are effective and catch any errors or bugs in your code. In this blog post, we will discuss what code coverage is and why you should strive for maximum coverage in your tests. We will also provide some recommendations on how to achieve this.
Choosing a best-suited automation tool for mobile apps testing becomes reasonably important for improving application speed and getting a better response. This blog highlights the most efficient mobile app testing tools used to carry out various application testing processes efficiently and effectively.
Effective testing is only possible when the most appropriate and readily available tool is identified. This blog will walk you through some of the most popular automation solutions available in the market for Web Testing.
Choosing a best-suited automation tool for the Desktop apps becomes reasonably important when the developers work over sophisticated legacy systems in complex enterprise environments. This blog discusses the finest Automation tools that automate the desktop app’s functional testing.
Testing APIs is an integral part of the testing process. Testing business logic pertains to the interaction between a user interface and underlying data and is part of the business layer. An API test pertains to a process of verifying the functionality, performance, and robustness of an API.
The terms “automated testing” and “continuous testing” are frequently used together. Although they work well together, they are not identical. Each of the two methods of automated testing and continuous testing have a significant impact on DevOps and Continuous Delivery.
In automation testing, you must know which test you need to automate or select the appropriate tool for your automation testing. Automation testing provides you with a wide dimension to explore new opportunities in testing and product development.
A few years back, most of the testing cycles were performed by replicating the ideal testing environment. And to complete the testing, engineers used to require many manual UI tests following test scripts. But it was very time taking, and time-to-market was often affected by this. But now, companies are working with rapid development models and follow short release cycles. Companies have also replaced the conventional methods of manual testing with automation. UI test automation has become a norm.
The microservice architecture paradigm is constructing an application by breaking it into small independent services. Each operates in its process and communicates with the others through a most typically HTTP API. These services are entirely autonomous in their deployment and operation.Testing a microservice architecture has its own challenges and strategies which we will outline in this blogpost.
Having a reliable QA strategy is important for the smooth functioning of the software. While there are software testing methods that utilize the latest technological advancements to pinpoint bugs, save time, and run various test scenarios, adding Artificial Intelligence (AI) and Machine Learning (ML) to the QA process takes it to a next level enabling businesses to enhance their testing process.
Mobile app testing has some specific characteristics beyond cross-browser testing that are hard to tackle. Let’s talk about the most important factors you need to consider while testing your mobile apps.
The majority of your website’s visitors will access it using a browser. Your website code is interpreted differently by each browser, which means that it may seem different to visitors who use different browsers when they visit your website. For example, you should avoid relying on a browser to detect a content type or encoding correctly when you did not specify one.
We are living in the tech era, and we are dependent on many web applications. The best testing efforts are required to create a quality and efficient web application. Testing web applications is altogether a tedious task, and it also consumes time. It is important to adopt automation testing to reduce such efforts, as it saves a lot of time and effort for the testing team. Testers can pay attention to more human perspective-related tasks and can leave repetitive tasks to automation.
Automating software testing is gaining traction in the industry due to its several advantages. In addition to saving time, automation also eliminates the possibility of human error. It is possible today to automate a wide range of test scripts using various tools. However, it is crucial to use the right testing tool to succeed with your testing efforts.