Category: Data

Revolutionizing L3 ADAS: Harnessing the Power of Test Harnesses and MLOps for Safe and Reliable Automotive Technology

Regression testing is a crucial aspect of developing L3 Advanced Driver Assistance Systems (ADAS) technology. It involves re-testing the entire system or parts of it, after changes or modifications have been made, to ensure that the changes did not introduce any new bugs or defects. This is particularly important for ADAS systems, which rely on…
Read more

Javascript, Caching to Optimize Network Traffic

Browsers use caching to temporarily store resources locally on the device, such as HTML, CSS, and JavaScript files, images, and videos. This allows the browser to quickly access the resources without having to make additional requests to the server. One way browsers can enable device-side caching is through the use of local storage. Local storage…
Read more

Training PackNet-SFM with RGB + PointCloud Data

Fusing time synchronized RGB camera images with point cloud data is a powerful approach for training a PackNet-SFM (Structure from Motion) model in PyTorch. This technique combines the benefits of both RGB images and point cloud data to improve the accuracy and robustness of the SFM model. In this article, we will discuss the various…
Read more

Why Overfitting Data is a Handicap for ADAS Deployment

ADAS enabled vehicles are most commonly driven on highways and main roads for a number of reasons. One reason is that these types of roads tend to have less complex driving scenarios compared to residential areas or side roads. Highways and main roads often have fewer intersections and more predictable traffic patterns, which can make…
Read more

Data backhauling tips and techniques to save on bandwidth & latency

Data backhauling refers to the process of transferring data from one location to another, typically from a remote or geographically dispersed location to a central location or “backhaul.” This process is often used in industries such as transportation, where data from vehicles or other mobile assets is collected and sent back to a central location…
Read more

Training a Model in MLFlow from CVAT label data

CVAT (Computer Vision Annotation Tool) is an open source tool developed by Intel that allows users to label and annotate images and video data for training machine learning models. MLFlow is an open source platform for managing the end-to-end machine learning lifecycle. It provides tools for tracking experiment runs, organizing code, and reproducing runs, among…
Read more

Integrating CVAT annotation into MLFlow

CVAT (Computer Vision Annotation Tool) is an open-source annotation tool for computer vision tasks that allows users to label and manage large datasets quickly and efficiently. Integrating CVAT with an MLFlow framework can streamline the data labeling process and make it easier to track and analyze the performance of your machine learning models. Here is…
Read more

Dimensionality reduction and how it helps reduce the search space by leveraging known information

Removing dimensions or making invariant features is a technique used to reduce the search space in a problem by eliminating certain variables or making them irrelevant. This can be especially useful in LiDAR slam, which has a 6Dof search space (x, y, z, roll, pitch, yaw). By reducing the dimensions, the number of permutations in…
Read more

Data balancing to remove data bias, do a deep dive on different approaches

Data balancing is the process of ensuring that a machine learning dataset is representative of the real-world population from which it is drawn. This is important because if a dataset is biased, then the machine learning model that is trained on that dataset will also be biased. Bias in machine learning models can lead to…
Read more

How data structures impact time complexity of code

Data structures are the foundation of efficient algorithms and play a crucial role in determining the time complexity of a piece of code. Time complexity refers to the amount of time it takes for an algorithm to complete, and it is a measure of how the runtime of an algorithm grows as the input size…
Read more

Techniques to Boost True Positive Rates using Independent Combinatorics

True positive rates, or the proportion of positive cases that are correctly identified, are an important consideration in many areas. One way to boost true positive rates is to utilize independent combinatorics, a set of techniques that involve combining multiple independent pieces of information or evidence to make a decision. Here are some specific techniques…
Read more

Loose Coupling vs Tight Coupling; Best of Both Worlds

Loose coupling and tight coupling refer to the degree of interdependence between different components in a system. In software development, loose coupling refers to the design of components that can operate independently of one another and do not rely heavily on the internal details of other components. Tight coupling, on the other hand, refers to…
Read more

Message Queues in Multi-Threaded Applications

Message queues are a software component that allow different parts of a system, or different systems, to communicate with each other by passing messages. They are often used in architectures that are distributed, meaning that they consist of multiple independent systems that need to communicate with each other. One common use case for message queues…
Read more

Wheel Odometer and How it Helps Calibration of Accelerometer

Wheel odometry is a method used to measure the distance traveled by a vehicle by tracking the rotations of its wheels. This can be done through various methods such as using encoders, sensors, or by measuring the speed of the wheels using an OBD (on-board diagnostics) sensor. One of the main applications of wheel odometry…
Read more

ROS 1 vs ROS 2 Tradeoffs and Advantages

ROS (Robot Operating System) is a popular open-source robotics framework that provides libraries and tools for building robot applications. There are currently two versions of ROS: ROS 1 and ROS 2. In this article, we will explore the tradeoffs and advantages of both versions and discuss the tools available for converting between them. We will…
Read more

Scope of noise and how to expand it

Noise is an inherent part of any machine learning (ML) model development process. It refers to any random or unpredictable variations in the data that can impact the accuracy of the model. Noise can come from a variety of sources, including measurement errors, data quality issues, and even the sampling process itself. In the process…
Read more