IRIS: Integrated Retinal Functionality in Image Sensors
Zihan Yin, Md Abdullah-Al Kaiser, Lamine Ousmane Camara, Mark, Camarena, Maryam Parsa, Ajey Jacob, Gregory Schwartz, Akhilesh Jaiswal

TL;DR
IRIS introduces a novel co-designed neuromorphic image sensor that replicates retinal motion computations, enabling efficient, real-time vision processing for dynamic environments using advanced semiconductor technology.
Contribution
The paper presents a new technology-circuit co-design implementing retinal motion computations in image sensors, leveraging recent semiconductor stacking advances.
Findings
Simulations show feasibility on 22nm technology node.
Proposed circuits enable real-time motion processing.
Potential for high-speed, energy-efficient vision applications.
Abstract
Neuromorphic image sensors draw inspiration from the biological retina to implement visual computations in electronic hardware. Gain control in phototransduction and temporal differentiation at the first retinal synapse inspired the first generation of neuromorphic sensors, but processing in downstream retinal circuits, much of which has been discovered in the past decade, has not been implemented in image sensor technology. We present a technology-circuit co-design solution that implements two motion computations occurring at the output of the retina that could have wide applications for vision based decision making in dynamic environments. Our simulations on Globalfoundries 22nm technology node show that, by taking advantage of the recent advances in semiconductor chip stacking technology, the proposed retina-inspired circuits can be fabricated on image sensing platforms in existing…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Memory and Neural Computing · CCD and CMOS Imaging Sensors · Neuroscience and Neural Engineering
