Category: Autonomous Driving

Integrating Federated Learning into CVAT & MLFlow

Federated learning is a machine learning technique that enables the training of models on decentralized data, without the need for the data to be centralized in one location. Instead, data is distributed across a number of different devices or edge devices, such as smartphones or IoT devices, and the model is trained by aggregating updates…
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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…
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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…
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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…
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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…
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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…
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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…
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Camera Calibration: Tips and Techniques

Camera calibration is the process of determining the intrinsic and extrinsic parameters of a camera. Intrinsic parameters are properties of the camera itself, such as its focal length and principal point, while extrinsic parameters describe the position and orientation of the camera in the world. Accurate calibration is important for tasks such as 3D reconstruction,…
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