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Software Pipeline in Safer Autonomous Vehicles – Part 2

For autonomous vehicles (AV) to perform at par with human ability, we first need to understand human driving behaviour. For simplification, human driving tasks can be broken down into two categories of tasks, i.e., the ‘what tasks’ and the ‘how tasks’, together referred to as the orthogonal tasks. The driving task under the ‘what category’ can be further broken down ...

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Software Pipeline in Safer Autonomous Vehicles – Part 1

Safety concern in an autonomous vehicles (AV) primarily arises from the software pipeline which has successfully replaced the human driver, who earlier acted as an integrator and operator of various driving tasks. AV need to perform multiple highly dynamic and complex tasks for which they should be able to generalise any unpredictable situation and this process primarily depends on its ...

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Part-of-Speech Tagging using Hidden Markov Models

Parts of Speech (POS) tagging is a text processing technique to correctly understand the meaning of a text. POS tagging is the process of assigning the correct POS marker (noun, pronoun, adverb, etc.) to each word in an input text. We discuss POS tagging using Hidden Markov Models (HMMs) which are probabilistic sequence models.

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Machine Learning in a Nonlinear World: a Linear Explanation through the Domain of the Autonomous Vehicles

The use of machine learning (ML) algorithms is becoming common in safety-critical autonomous systems (AS) such as autonomous vehicles and advanced robotic tasks. These systems are nonlinear and interact with nonlinear (dynamic) environments, resulting in stochastic outcomes. In this post, we introduce how ML is applied to such dynamic systems, more specifically for the autonomous vehicles, and a first discussion ...

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