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Found 9 papers, 1 papers with code
HermEIS: A Parallel Multichannel Approach to Rapid Spectral Characterization of Neural MEAs
The promise of increasing channel counts in high density ($> 10^4$) neural Microelectrode Arrays (MEAs) for high resolution recording comes with the curse of developing faster characterization strategies for concurrent acquisition of multichannel electrode integrities over a wide frequency spectrum.
Pix2HDR -- A pixel-wise acquisition and deep learning-based synthesis approach for high-speed HDR videos
By combining the versatility of pixel-wise sampling patterns with the strength of deep neural networks at decoding complex scenes, our method greatly enhances the vision system's adaptability and performance in dynamic conditions.
Neuromorphic Place Cells
We demonstrate a mixed-mode implementation for spatial encoding neurons including theta cells, vector cells, and place cells.
Prospective Learning: Principled Extrapolation to the Future
We conjecture that certain sequences of tasks are not retrospectively learnable (in which the data distribution is fixed), but are prospectively learnable (in which distributions may be dynamic), suggesting that prospective learning is more difficult in kind than retrospective learning.
A Neuromorphic Proto-Object Based Dynamic Visual Saliency Model with an FPGA Implementation
The ability to attend to salient regions of a visual scene is an innate and necessary preprocessing step for both biological and engineered systems performing high-level visual tasks (e. g. object detection, tracking, and classification).
Large-Scale Neuromorphic Spiking Array Processors: A quest to mimic the brain
Neuromorphic engineering (NE) encompasses a diverse range of approaches to information processing that are inspired by neurobiological systems, and this feature distinguishes neuromorphic systems from conventional computing systems.
Bioinspired Visual Motion Estimation
Visual motion estimation is a computationally intensive, but important task for sighted animals.
Fast Neuromimetic Object Recognition using FPGA Outperforms GPU Implementations
Recognition of objects in still images has traditionally been regarded as a difficult computational problem.
HFirst: A Temporal Approach to Object Recognition
The asynchronous nature of these systems frees computation and communication from the rigid predetermined timing enforced by system clocks in conventional systems.
