1. [Publications](/index.php/publications) 2. Alpha-Vision: A Real-Time Always-on Vision Processor with 787µs Face Detection Latency in <5mW # Alpha-Vision: A Real-Time Always-on Vision Processor with 787µs Face Detection Latency in <5mW ![](/sites/default/files/styles/wide/public/publications/alphavision.jpg?itok=Z2VcIFKZ) ALPhA-Vision is an always-on low-power subsystem for DNN-inference-based vision tasks in edge SoCs. Flexible and programmable, the subsystem supports CNN and ViT inference and employs hardware/software co-design to enable fully end-to-end execution with no external memory accesses. Fine-grained power management features to mitigate leakage enable the subsystem to perform face detection with 787µs latency and 99.3% detection accuracy with 4.6 mW average power at 60fps. ## Authors [Ben Keller](/index.php/person/ben-keller) [Rangharajan Venkatesan](/index.php/person/rangharajan-venkatesan) [Steve Dai](/index.php/person/steve-dai) [Jason Clemons](/index.php/person/jason-clemons) [Matt Fojtik](/index.php/person/matt-fojtik) [Muya Chang](/index.php/person/muya-chang) Thierry Tambe (Stanford University) [Nathaniel Pinckney](/index.php/person/nathaniel-pinckney) [Stephen Tell](/index.php/person/stephen-tell) [Qijing Jenny Huang](/index.php/person/qijing-jenny-huang) [Shalini De Mello](/index.php/person/shalini-de-mello) [Brucek Khailany](/index.php/person/brucek-khailany) ## Publication Date Monday, February 16, 2026 ## Published in [ISSCC 2026](https://www.isscc.org/) ## Research Area [Artificial Intelligence and Machine Learning ](/index.php/research-area/machine-learning-artificial-intelligence) [Circuits and VLSI Design](/index.php/research-area/circuits) [Computer Architecture](/index.php/research-area/computer-architecture) [Computer Vision](/index.php/research-area/computer-vision) ## External Links [Paper](https://ieeexplore.ieee.org/document/11409322) ## Copyright This material is posted here with permission of the IEEE. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to .