We are excited to be part of #ICRA2024 (May 13th-17th) showcasing SceneControl: Diffusion for Controllable Traffic Scene Generation (May 16, 4:30pm-6:00pm) and QuAD: Query-based Interpretable Neural Motion Planning for Autonomous Driving (May 16, 10:30am-12:00pm). Check out the papers here: https://lnkd.in/gR4gAWqY, https://waabi.ai/quad/
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Build Predictive Models | Data Analyst | Co-Founder of Costrick | Designing Nalyst Library | YouTube @AnalyticalHarry
In a tutorial by Lex Fridman on self-driving cars, semantic segmentation is explored as a technique involving the labeling of each pixel in an image with a class that represents what is depicted. This technique is important for understanding scenes in applications such as autonomous driving. The evaluation of metrics in semantic segmentation, such as pixel accuracy and Intersection over Union (IoU), is conducted to assess performance. Link to Lex Fridman github: https://lnkd.in/eGgDmbbM #datascience #machinelearning #deeplearning #ml #dl #neuralnets #selfdrivingcar
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Join #APAC's upcoming webinar on the MLPerf® Automotive Benchmark by MLCommons. Set for August 1st, this event showcases a new AI benchmark for autonomous vehicles, including an SSD-ResNet50 demo. It's a great opportunity for automotive professionals to explore the latest in AI benchmarking and interact with industry experts. Register: https://lnkd.in/ex-tFvnk #MLPerf #AutomotiveAI #AutonomousVehicles #MLCommons #AI #Benchmark
Attention APAC Automotive Industry Leaders - Join the "Revolutionizing Automotive AI with MLPerf® Automotive Benchmark" Webinar on August 1st. We invite #APAC industry leaders to explore the MLPerf® #Automotive #Benchmark POC, a groundbreaking #AI benchmark for #autonomousvehicles. Highlights include an introduction to the benchmark, key features like camera-based object detection, a live SSD-ResNet50 demo, and insights on industry collaboration. Engage with experts from MLCommons® and Autonomous Vehicle Computing Consortium, Inc. (AVCC), stay updated on AI advancements, and help shape future benchmarks. Don't miss out – register now! https://lnkd.in/ex-tFvnk
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Tune in as we explore the thrilling future of automotive AI with Shanton Wilcox in this on-demand session. Learn about the incredible advancements in autonomous driving and AI's impact on safety & maintenance: http://bit.ly/3Y36XVy #AIDriven #TechnologyRevolution #NTTDATA
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Large dataset for autonomous driving and ADAS development? Unlabeled. But, no efficient way to find all the 🐕dogs walking in the park🐩 in the dataset for labeling? 🐶 Check out Quasara Plato searching for anything in datasets with natural language. #dataexploration on raw, unlabelled image or video data. A Big Thank You to AUDI AG for open sourcing their a2d2 dataset, propelling our R&D. Sources: https://www.a2d2.audi/ https://lnkd.in/eUXSn_tU https://lnkd.in/eAVExMDG #autonomousdriving #ADAS #dataintelligence #semanticsearch #understandrawdata #dataexploration #dataacquisition #computervision #dogs #datatransparency
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Discover how Split Pixel HDR Technology in embedded vision offers higher dynamic range and superior image quality without motion blur. This technology works by splitting each pixel on the sensor into two sub-pixels to capture the brighter and darker areas of the scene. Dive into the future of precision imaging for industrial automation, autonomous vehicles, and medical applications. Read more - https://lnkd.in/g6Ktc_8c #TechInnovation #EmbeddedVision #SplitPixelTechnology #TechAdvancements #EmbeddedCameras
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🌐 Unlock the power of HTTPS & WebSocket for Machine Learning! 🌟 Explore our latest blog to discover how these protocols enhance the security and efficiency of real-time applications. 👉🏻 Learn: ✅ How does these protocols help in Machine Learning ✅ Real-world use cases from autonomous vehicles to video analytics ✅ Advantages and practical applications 🔗 Link to blog: https://lnkd.in/gkXwRVzi
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Revolutionizing Transportation: AI Cameras and Autonomous Driving with CEO Chris Piche | Ep 901 Tune in to explore how AI cameras are set to revolutionize transportation, making roads safer and more efficient for everyone. Listen to the full episode here: https://lnkd.in/gaXQDQyv
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DriveGenVLM: Advancing Autonomous Driving with Generated Videos and Vision Language Models VLMs Integrating advanced predictive models into autonomous driving systems has become crucial for enhancing safety and efficiency. Camera-based video prediction emerges as a pivotal component, offering rich real-world data. Content generated by artifici... https://lnkd.in/enrmHNSD #AI #ML #Automation
DriveGenVLM: Advancing Autonomous Driving with Generated Videos and Vision Language Models VLMs
openexo.com
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Amazing Course. Loving the experience exploring autonomous driving - object detection and face recognition using CNN. Thanks to Andrew and the Team giving use such a nice course to learn. DeepLearning.AI
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👨💻 Tech Whisperer | 🚀 Exploring the digital frontier, one line of code at a time | 💡 Innovator at heart | 🤖 AI aficionado | #TechLife
MDHA Enhances Multi-View 3D Detection with Hybrid Anchors and Circular Deformable Attention! *** MDHA's hybrid anchor approach pairs 2D center coordinates with depth predictions to form 2.5D anchors, projecting them into 3D proposals. That reduces reliance on good anchor initialization and enhances adaptability to various driving scenarios. The Circular Deformable Attention mechanism efficiently spans multi-view inputs, treating them as a contiguous 360° image, allowing reference points to attend to adjacent images. That improves efficiency and accuracy in detecting objects from multiple views, making MDHA a significant advancement in autonomous driving technology. *** https://lnkd.in/erpYJ93Q
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