ISBN: 9798180774019 - automotive ai integration: on-board machine learning for adas sensor fusion, predictive systems, and in-vehicle intelligence (software-defined vehicle engineering series) (6 Ergebnisse)

Sprache: Englisch
Verlag: Independently Published Jun 2026, 2026
Serie: Buch 6 von 9 - Software-Defined Vehicle Engineering Series
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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Taschenbuch. Zustand: Neu. Neuware - Master the Art of Production-Ready Vehicle IntelligenceAs automotive engineering transitions to software-defined architectures, integrating reliable, high-performance machine learning is the ultimate competitive advantage. Automotive AI Integration is the definitive engineering guide to deploying robust on-board ML models inside production vehicles.Written specifically for automotive embedded engineers, ADAS developers, and AI researchers, this comprehensive manual bridges the gap between theoretical deep learning and real-world physical deployment. Learn how to navigate the complex trade-offs of performance, safety, and hardware constraints using industry-standard frameworks.Inside this masterclass, you will discover: - Silicon-Level Optimization: Master neural network inference on leading SoCs like NVIDIA DRIVE Orin, Qualcomm Snapdragon Ride, and Mobileye EyeQ Ultra.- Advanced Model Compression: Implement model quantization (INT8/FP8), pruning, and TensorRT compilation to fit large models into tight automotive resource budgets.- Safety & Standards: Design MISRA C++ compliant machine learning pipelines and build robust ISO 26262 safety cases up to ASIL-D.- Sensor Fusion Architectures: Combine camera Bird's-Eye-View (BEV), radar point clouds, and LiDAR data inside modern deep neural networks.- AUTOSAR & OTA Integration: Deploy models as AUTOSAR Adaptive software components and architect secure, failsafe over-the-air (OTA) update pipelines.- Next-Gen Cockpit Intelligence: Build highly responsive Driver Monitoring Systems (DMS) and deploy local, low-latency LLM voice assistants on-edge.Whether you are developing Level 2+ ADAS features or architecting Level 4 autonomous systems, this book provides the production-validated patterns, testing paradigms, and validation frameworks you need to write safe, efficient, and regulatory-compliant automotive software.…

Sprache: Englisch
Verlag: Independently Published, 2026
Serie: Buch 6 von 9 - Software-Defined Vehicle Engineering Series
- Softcover
- Print-on-Demand
Anbieter: Grand Eagle Retail, Bensenville, IL, USAGrand Eagle Retail
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Paperback. Zustand: new. Paperback. Master the Art of Production-Ready Vehicle IntelligenceAs automotive engineering transitions to software-defined architectures, integrating reliable, high-performance machine learning is the ultimate competitive advantage. Automotive AI Integration is the definitive engineering guide to deploying robust on-board ML models inside production vehicles.Written specifically for automotive embedded engineers, ADAS developers, and AI researchers, this comprehensive manual bridges the gap between theoretical deep learning and real-world physical deployment. Learn how to navigate the complex trade-offs of performance, safety, and hardware constraints using industry-standard frameworks.Inside this masterclass, you will discover: Silicon-Level Optimization: Master neural network inference on leading SoCs like NVIDIA DRIVE Orin, Qualcomm Snapdragon Ride, and Mobileye EyeQ Ultra.Advanced Model Compression: Implement model quantization (INT8/FP8), pruning, and TensorRT compilation to fit large models into tight automotive resource budgets.Safety & Standards: Design MISRA C++ compliant machine learning pipelines and build robust ISO 26262 safety cases up to ASIL-D.Sensor Fusion Architectures: Combine camera Bird's-Eye-View (BEV), radar point clouds, and LiDAR data inside modern deep neural networks.AUTOSAR & OTA Integration: Deploy models as AUTOSAR Adaptive software components and architect secure, failsafe over-the-air (OTA) update pipelines.Next-Gen Cockpit Intelligence: Build highly responsive Driver Monitoring Systems (DMS) and deploy local, low-latency LLM voice assistants on-edge.Whether you are developing Level 2+ ADAS features or architecting Level 4 autonomous systems, this book provides the production-validated patterns, testing paradigms, and validation frameworks you need to write safe, efficient, and regulatory-compliant automotive software. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Sprache: Englisch
Verlag: Independently published, 2026
Serie: Buch 6 von 9 - Software-Defined Vehicle Engineering Series
- Softcover
- Print-on-Demand
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PAP. Zustand: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Sprache: Englisch
Verlag: Independently published, 2026
Serie: Buch 6 von 9 - Software-Defined Vehicle Engineering Series
- Softcover
- Print-on-Demand
Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes KönigreichPBShop.store UK
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PAP. Zustand: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Sprache: Englisch
Verlag: Independently published, 2026
Serie: Buch 6 von 9 - Software-Defined Vehicle Engineering Series
- Softcover
- Print-on-Demand
Anbieter: California Books, Miami, FL, USACalifornia Books
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Zustand: New. Print on Demand.

Sprache: Englisch
Verlag: Independently Published, 2026
Serie: Buch 6 von 9 - Software-Defined Vehicle Engineering Series
- Softcover
- Print-on-Demand
Anbieter: CitiRetail, Stevenage, Vereinigtes KönigreichCitiRetail
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Paperback. Zustand: new. Paperback. Master the Art of Production-Ready Vehicle IntelligenceAs automotive engineering transitions to software-defined architectures, integrating reliable, high-performance machine learning is the ultimate competitive advantage. Automotive AI Integration is the definitive engineering guide to deploying robust on-board ML models inside production vehicles.Written specifically for automotive embedded engineers, ADAS developers, and AI researchers, this comprehensive manual bridges the gap between theoretical deep learning and real-world physical deployment. Learn how to navigate the complex trade-offs of performance, safety, and hardware constraints using industry-standard frameworks.Inside this masterclass, you will discover: Silicon-Level Optimization: Master neural network inference on leading SoCs like NVIDIA DRIVE Orin, Qualcomm Snapdragon Ride, and Mobileye EyeQ Ultra.Advanced Model Compression: Implement model quantization (INT8/FP8), pruning, and TensorRT compilation to fit large models into tight automotive resource budgets.Safety & Standards: Design MISRA C++ compliant machine learning pipelines and build robust ISO 26262 safety cases up to ASIL-D.Sensor Fusion Architectures: Combine camera Bird's-Eye-View (BEV), radar point clouds, and LiDAR data inside modern deep neural networks.AUTOSAR & OTA Integration: Deploy models as AUTOSAR Adaptive software components and architect secure, failsafe over-the-air (OTA) update pipelines.Next-Gen Cockpit Intelligence: Build highly responsive Driver Monitoring Systems (DMS) and deploy local, low-latency LLM voice assistants on-edge.Whether you are developing Level 2+ ADAS features or architecting Level 4 autonomous systems, this book provides the production-validated patterns, testing paradigms, and validation frameworks you need to write safe, efficient, and regulatory-compliant automotive software. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…