Exploiting large neuroimaging datasets to create connectome-constrained approaches for more robust, efficient, and adaptable artificial intelligence
EC Johnson, BS Robinson… - … Learning for Multi …, 2023 - spiedigitallibrary.org
Despite the progress in deep learning networks, efficient learning at the edge (enabling
adaptable, low-complexity machine learning solutions) remains a critical need for defense …
adaptable, low-complexity machine learning solutions) remains a critical need for defense …
[HTML][HTML] A Novel Semi-automated Proofreading and Mesh Error Detection Pipeline for Neuron Extension
J Joyce, R Chalavadi, J Chan, S Tanna, D Xenes… - bioRxiv, 2023 - ncbi.nlm.nih.gov
The immense scale and complexity of neuronal electron microscopy (EM) datasets pose
significant challenges in data processing, validation, and interpretation, necessitating the …
significant challenges in data processing, validation, and interpretation, necessitating the …
Data-driven motif discovery in biological neural networks
Data from a variety of domains are represented as graphs, including social networks,
transportation networks, computer networks, and biological networks. A key question spans …
transportation networks, computer networks, and biological networks. A key question spans …