Image classification

18x faster MobileNetV3 on TI-TDA4VM

Texas Instruments' MobileNetV3LiteLarge model, optimized with Embedl's hardware-aware SDK, achieves an 18x speed boost and 10% higher accuracy on the TI TDA4 platform. This showcases the power of tailoring AI models to specific hardware for optimal performance.

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Kodiak Embedl (1)-min

Embedl Turbocharges Kodiak’s GenAI Edge Deployment

Leading autonomous trucking company Kodiak Robotics works with Embedl’s edge AI tools to effortlessly deploy generative AI models across multiple hardware platforms.

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Vision Transformers-min

Optimizing Vision Transformers for Peak Performance on Nvidia Jetson AGX Orin

In this case study, we'll explore how we optimized the Vision Transformer model to run efficiently on the Nvidia Jetson AGX Orin hardware platform using Embedl's Model Optimization SDK.

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Segment-min

Semantic Segmentation in real-time on TI’s TDA4VM

In this case study, we will focus on the Lightweight Atrous Spatial Pyramid Pooling (LRASPP) model, an architecture specifically designed for efficient semantic segmentation on mobile and embedded platforms.

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Lane detection-min (1)

6x Faster Ultra Fast Lane Detection v2 on TI TDA4VM

In this case study, we'll explore how we optimized the Ultra Fast Lane Detection v2 model to run efficiently on the Texas Instruments TDA4VM hardware platform using Embedl's Model Optimization SDK.

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Blog & events (45)-min

Driver Monitoring Systems

Time efficiency is a major advantage of integrating edge AI tools in the development pipeline. Embedl’s “always-on” functionality within the CI/CD system accelerates development workflows.

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