Yu Liu
Texas A&M University
13 Papers
65 Citations
Yu Liu is an academic researcher from Texas A&M University. The author has contributed to research in topics: Spiking neural network & Liquid state machine. The author has an hindex of 6, co-authored 11 publications.
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Papers
•Posted Content
Improved Techniques for Learning to Dehaze and Beyond: A Collective Study
Yu Liu,Guanlong Zhao,Boyuan Gong,Yang Li,Ritu Raj,Niraj Goel,Satya Kesav,Sandeep Gottimukkala,Zhangyang Wang,Wenqi Ren,Dacheng Tao +10 more
TL;DR: Two related but important tasks based on the recently released REalistic Single Image DEhazing (RESIDE) benchmark dataset are explored: (i) single image dehazing as a low-level image restoration problem and (ii) high-level visual understanding of hazy images.
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SSO-LSM: A Sparse and Self-Organizing architecture for Liquid State Machine based neural processors
Yingyezhe Jin,Yu Liu,Peng Li +2 more
- 18 Jul 2016
TL;DR: A novel Sparse and Self-Organizing LSM (SSO-LSM) architecture with a low-overhead hardware-friendly Spike-Timing Dependent Plasticity (STDP) mechanism for efficient on-chip reservoir tuning and induces desirable self-organizing behaviors in the reservoir that naturally lead to a sparser recurrent network.
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Spike-Train Level Direct Feedback Alignment: Sidestepping Backpropagation for On-Chip Training of Spiking Neural Nets
TL;DR: A novel spike-train level direct feedback alignment (ST-DFA) algorithm is proposed, which is much more bio-plausible and hardware friendly than BP and shows excellent performance vs. overhead tradeoffs for real-world speech and image classification applications.
Energy-efficient FPGA Spiking Neural Accelerators with Supervised and Unsupervised Spike-timing-dependent-Plasticity
TL;DR: This article explores bio-plausible spike-timing-dependent-plasticity (STDP) mechanisms to train liquid state machine models with and without supervision and pursues efficient hardware implementation of FPGA LSM accelerators by performing algorithm-level optimization of the two proposed training rules and exploiting the self-organizing behaviors naturally induced by STDP.
Melatonin protects against maternal diabetes-associated meiotic defects by maintaining mitochondrial function.
TL;DR: In this paper , the pineal gland synthesized by pineal glands has been shown to have beneficial effects on oocyte quality owing to its antioxidative function, and the exposure of oocytes of diabetic mice to melatonin, in vitro , alleviated aberrant oocyte maturation competence.
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