Development Tools for Embedded Vision
ENCOMPASSING MOST OF THE STANDARD ARSENAL USED FOR DEVELOPING REAL-TIME EMBEDDED PROCESSOR SYSTEMS
The software tools (compilers, debuggers, operating systems, libraries, etc.) encompass most of the standard arsenal used for developing real-time embedded processor systems, while adding in specialized vision libraries and possibly vendor-specific development tools for software development. On the hardware side, the requirements will depend on the application space, since the designer may need equipment for monitoring and testing real-time video data. Most of these hardware development tools are already used for other types of video system design.
Both general-purpose and vender-specific tools
Many vendors of vision devices use integrated CPUs that are based on the same instruction set (ARM, x86, etc), allowing a common set of development tools for software development. However, even though the base instruction set is the same, each CPU vendor integrates a different set of peripherals that have unique software interface requirements. In addition, most vendors accelerate the CPU with specialized computing devices (GPUs, DSPs, FPGAs, etc.) This extended CPU programming model requires a customized version of standard development tools. Most CPU vendors develop their own optimized software tool chain, while also working with 3rd-party software tool suppliers to make sure that the CPU components are broadly supported.
Heterogeneous software development in an integrated development environment
Since vision applications often require a mix of processing architectures, the development tools become more complicated and must handle multiple instruction sets and additional system debugging challenges. Most vendors provide a suite of tools that integrate development tasks into a single interface for the developer, simplifying software development and testing.

Qualcomm at Embedded World: Accelerating Digital Transformation with Edge AI
This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. An essential partner to the embedded community, Qualcomm Technologies, Inc. strengthens its leadership in intelligent computing with several key announcements The AI revolution is sparking a wave of innovation in the embedded community, spawning a flurry of

Synaptics Extends Edge AI Portfolio with High-performance Adaptive MCUs for Multimodal Context-aware Computing
Featuring three power levels, the SR-Series MCUs scale Astra AI-Native hardware and open-source software to accelerate the development of low-power, cognitive IoT devices. Nuremberg, Germany, March 10, 2025 — Synaptics® Incorporated (Nasdaq: SYNA) has extended its award-winning Synaptics AstraTM AI-Native platform with the SR-Series high-performance adaptive microcontroller units (MCUs) for scalable context-aware Edge AI. The

AutoML Decoded: The Ultimate Guide and Tools Comparison
This article was originally published at Tryolabs’ website. It is reprinted here with the permission of Tryolabs. The quest for efficient and user-friendly solutions has led to the emergence of a game-changing concept: Automated Machine Learning (AutoML). AutoML is the process of automating the tasks involved in the entire Machine Learning lifecycle, such as data

Zero-Shot AI: The End of Fine-tuning as We Know It?
This article was originally published at Tenyks’ website. It is reprinted here with the permission of Tenyks. Models like SAM 2, LLaVA or ChatGPT can do tasks without special training. This has people wondering if the old way (i.e., fine-tuning) of training AI is becoming outdated. In this article, we compare two models: YOLOv8 (fine-tuning)

Axelera AI Secures Up to €61.6 Million Grant to Develop Scalable AI Chiplet for High-performance Computing
March 6, 2025 – Axelera AI, the leading provider of purpose-built AI hardware acceleration technology for generative AI and computer vision inference at the edge, unveiled Titania™, a high-performance, energy efficient and scalable AI inference chiplet. The development of this chiplet builds on Axelera AI’s innovative approach to Digital In-Memory Computing (D-IMC) architecture, which provides

Unveiling the Qualcomm Dragonwing Brand Portfolio: Solutions For a New Era of Industrial Innovation
This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. Our mission is to deliver intelligent computing everywhere. We have an amazing suite of products, and while you may be familiar with the Snapdragon brand portfolio, you may not know that we have a whole suite of

3LC: What is It and Who is It For?
This blog post was originally published at 3LC’s website. It is reprinted here with the permission of 3LC. AI performance isn’t just about better architectures or more compute – it’s about better data. Even perfectly labeled datasets can hold hidden inefficiencies that limit accuracy. See how teams use 3LC to refine datasets, optimize labeling strategies,

How e-con Systems’ TintE ISP IP Core Increases the Efficiency of Embedded Vision Applications
This blog post was originally published at e-con Systems’ website. It is reprinted here with the permission of e-con Systems. e-con Systems has developed TintE™, a ready to deploy ISP IP core engineered to enhance image quality in camera systems. Built to deliver high performance on leading FPGA platforms, it accelerates real-time image processing with