LEADER 04258nam 22005775 450 001 9910383844803321 005 20230302174912.0 010 $a1-4842-5722-7 024 7 $a10.1007/978-1-4842-5722-7 035 $a(CKB)4100000010659539 035 $a(DE-He213)978-1-4842-5722-7 035 $a(MiAaPQ)EBC6133719 035 $a(CaSebORM)9781484257227 035 $a(PPN)243229380 035 $a(OCoLC)1181958596 035 $a(OCoLC)on1181958596 035 $a(EXLCZ)994100000010659539 100 $a20200310d2020 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aReal-Time IoT Imaging with Deep Neural Networks $eUsing Java on the Raspberry Pi 4 /$fby Nicolas Modrzyk 205 $a1st ed. 2020. 210 1$aBerkeley, CA :$cApress :$cImprint: Apress,$d2020. 215 $a1 online resource (XXI, 224 p. 157 illus.) 311 $a1-4842-5721-9 327 $aChapter 1: Getting Started -- Chapter 2: Object Detection in Video Streams -- Chapter 3: Vision on Raspberry 4 -- Chapter 4: Analyzing Video Streams on the Raspberry -- Chapter 5: Vision and Home Automation.-. 330 $aThis book shows you how to build real-time image processing systems all the way through to house automation. Find out how you can develop a system based on small 32-bit ARM processors that gives you complete control through voice commands. Real-time image processing systems are utilized in a wide variety of applications, such as in traffic monitoring systems, medical image processing, and biometric security systems. In Real-Time IoT Imaging with Deep Neural Networks, you will learn how to make use of the best DNN models to detect object in images using Java and a wrapper for OpenCV. Take a closer look at how Java scripting works on the Raspberry Pi while preparing your Visual Studio code for remote programming. You will also gain insights on image and video scripting. Author Nicolas Modrzyk shows you how to use the Rhasspy voice platform to add a powerful voice assistant and completely run and control your Raspberry Pi from your computer. To get your voice intents for house automation ready, you will explore how Java connects to the MQTT and handles parametrized Rhasspy voice commands. With your voice-controlled system ready for operation, you will be able to perform simple tasks such as detecting cats, people, and coffee pots in your selected environment. Privacy and freedom are essential, so priority is given to using open source software and an on-device voice environment where you have full control of your data and video streams. Your voice commands are your own?and just your own. With recent advancements in the Internet of Things and machine learning, cutting edge image processing systems provide complete process automation. This practical book teaches you to build such a system, giving you complete control with minimal effort. You Will: Show mastery by creating OpenCV filters Execute a YOLO DNN model for image detection Apply the best Java scripting on Raspberry Pi 4 Prepare your setup for real-time remote programming Use the Rhasspy voice platform for handling voice commands and enhancing your house automation setup. 606 $aComputer input-output equipment 606 $aJava (Computer program language) 606 $aMachine learning 606 $aHardware and Maker$3https://scigraph.springernature.com/ontologies/product-market-codes/I29010 606 $aJava$3https://scigraph.springernature.com/ontologies/product-market-codes/I29070 606 $aMachine Learning$3https://scigraph.springernature.com/ontologies/product-market-codes/I21010 615 0$aComputer input-output equipment. 615 0$aJava (Computer program language). 615 0$aMachine learning. 615 14$aHardware and Maker. 615 24$aJava. 615 24$aMachine Learning. 676 $a004.7 700 $aModrzyk$b Nicolas$4aut$4http://id.loc.gov/vocabulary/relators/aut$0859276 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910383844803321 996 $aReal-Time IoT Imaging with Deep Neural Networks$92032235 997 $aUNINA