Title: MATLAB R2024b: A Review of the Latest Features and Enhancements Introduction: MATLAB, the high-level programming language and environment widely used for computational and numerical analyses, has released its latest version, MATLAB R2024b. Packed with new features and enhancements, this update aims to empower engineers, scientists, and students with improved tools and an enhanced user experience. In this article, we will review some of the notable additions in MATLAB R2024b and their potential impact on various applications. Enhanced Deep Learning: MATLAB R2024b brings significant advancements in deep learning capabilities, catering to the growing demands of AI and machine learning applications. The new Deep Network Designer, an interactive tool, allows users to easily create, train, and deploy deep learning models. With its intuitive drag-and-drop interface, users can design complex network architectures efficiently, making it easier to build and test neural networks. Image Processing and Computer Vision: For those involved in image processing and computer vision tasks, MATLAB R2024b offers a range of powerful updates. The new Video Labeler app supports semantic and instance segmentation labeling for video sequences. This feature simplifies the process of creating training datasets for computer vision models by providing accurate annotations and reducing manual effort. Additionally, the Image Labeler app now supports bounding box regression labeling, making it easier to train models for object detection and localization. Live Editor Enhancements: The Live Editor in MATLAB R2024b has been further enhanced, making it a more dynamic and intuitive tool for users. With new interactive controls and UI components, users can present data and results more effectively. The integration with MATLAB Online allows users to easily collaborate and share live scripts with others, enhancing the productivity and teamwork aspects of MATLAB-based projects. Furthermore, the auto-completion feature has been significantly improved, making code suggestions more accurate and context-aware. Automated Driving System Toolbox: The updated release of MATLAB also includes advancements in the Automated Driving System Toolbox, which is essential for autonomous vehicle development and testing. With R2024b, this toolbox now supports multimodal sensor fusion, enabling developers to combine data from various sensors such as radar, lidar, and cameras seamlessly. This integration enhances the accuracy and reliability of perception systems in autonomous vehicles, ensuring safer and more efficient driving experiences. Other Notable Features: In addition to the above-mentioned highlights, MATLAB R2024b includes several other important updates. The Aerospace Toolbox now provides enhanced support for flight simulation and analysis, including improved flight dynamics modeling and control systems design. The Robotics System Toolbox offers expanded coverage of robot manipulator modeling, enabling users to design and simulate complex robot manipulators easily. Moreover, various performance improvements have been implemented across the software, enhancing speed and memory management. Conclusion: MATLAB R2024b is a comprehensive update that brings several significant features and enhancements to MATLAB’s already impressive repertoire. From improved deep learning capabilities and advanced image processing tools to enhanced collaboration options and more efficient sensor fusion for autonomous vehicles, this release caters to a wide range of applications. MATLAB remains a powerful tool for engineers, scientists, and students, and the latest update further bolsters its position as the go-to platform for computational analysis and problem-solving.