Lattice Semiconductor

Lattice Semiconductor Demonstration of Speed Sign Detection Using ECP5 and Machine Learning

JP Singh, Automotive Marketing manager at Lattice Semiconductor, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Singh demonstrates a machine learning CNN implemented using the company’s sensAI stack on a ECP5 FPGA. Singh shows the detection of speed limit signs and the determination of speed limits with a CNN implementation that […]

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Lattice Semiconductor Demonstration of Object Counting Using ECP5 and Machine Learning

Dirk Seidel, Senior Industrial Marketing Manager at Lattice Semiconductor, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Seidel demonstrates object counting using machine learning with a CNN implementation based on Lattice’s sensAI stack and the ECP5 FPGA. Seidel shows how Lattice’s small form factor, low power and production-priced ECP5 FPGA can

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Lattice Semiconductor Demonstration of Human Presence Detection at the Edge

Tom Watzka, Marketing Manager and Mobile Systems Architect at Lattice Semiconductor, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Watzka demonstrates how the Lattice ECP5 FPGA can support Human Presence Inferencing at the IoT edge. This inferencing engine leverages the Lattice sensAI tool flow to deliver real-time performance with sub-1W power

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“Deep Quantization for Energy Efficient Inference at the Edge,” a Presentation from Lattice Semiconductor

Hoon Choi, Senior Director of Design Engineering at Lattice Semiconductor, presents the “Deep Quantization for Energy Efficient Inference at the Edge” tutorial at the May 2018 Embedded Vision Summit. Intelligence at the edge is different from intelligence in the cloud in terms of requirements for energy, cost, accuracy and latency. Due to limits on battery

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“Programmable CNN Acceleration in Under 1 Watt,” a Presentation from Lattice Semiconductor

Gordon Hands, Director of Marketing for IP and Solutions at Lattice Semiconductor, presents the "Programmable CNN Acceleration in Under 1 Watt" tutorial at the May 2018 Embedded Vision Summit. Driven by factors such as privacy concerns, limited network bandwidth and the need for low latency, system designers are increasingly interested in implementing artificial intelligence (AI)

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“Machine Learning Inference In Under 5 mW with a Binarized Neural Network on an FPGA,” a Presentation from Lattice Semiconductor

Abdullah Raouf, Senior Marketing Manager at Lattice Semiconductor, presents the “Machine Learning Inference In Under 5 mW with a Binarized Neural Network on an FPGA” tutorial at the May 2018 Embedded Vision Summit. The demand for always-on intelligence is rapidly increasing in various applications. You can find cameras that are always watching for anomalies in

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Solving Intelligence, Vision and Connectivity Challenges at the Edge with ECP5 FPGAs

This article was originally published at Lattice Semiconductor's website. It is reprinted here with the permission of Lattice Semiconductor. The rapid rise in the number of sensors that are being integrated into the current generation of embedded designs, as well as the integration of low cost cameras and displays, have opened the door to a

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Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.

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