Deep neural networks (DNNs) can achieve high accuracy when there is abundant training data that has the same distribution as the test data. In practical applications, data deficiency is often a ...

Volumetric functional imaging is widely used for recording neuron activities in vivo, but there exist tradeoffs between the quality of the extracted calcium traces, imaging speed, and laser power.

Convolutional neural networks (CNNs), which can recognize structural/configuration patterns in data with different architectures, have been studied for feature extraction. However, challenges remain ...

The first proof-of-concept pilot study with a limited-lead, rapid-response electroencephalogram medical device, which measures the electrical activity of the brain, and Vision Transformer, a ...

A novel hierarchical deep learning framework enables direct Desikan-Killiany brain parcellation using only diffusion ...

AI medical imaging market is projected to exceed $20B by 2035. Generative models address class imbalances in medical imaging ...

Work you complete in the non-credit experience will transfer to the for-credit experience when you upgrade and pay tuition. See How It Works for details. A previous version of Machine Learning: Theory ...

Use modern machine learning tools and python libraries. Explain how to deal with linearly-inseparable data. Compare logistic regression’s strengths and weaknesses. Explain what decision tree is & how ...

The recently published book Understanding Deep Learning by [Simon J. D. Prince] is notable not only for focusing primarily on the concepts behind Deep Learning — which should make it highly accessible ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

Deep learning high-content imaging is rapidly reshaping image-based screening in the modern laboratory environment. As high-content screening (HCS) generates increasingly large and complex datasets, ...