Deep learning convolutional neural networks generally involve multiple-layer, forward-backward propagation machine-learning algorithms that are computationally costly. In this work, we demonstrate an alternative
Here we present DeepPrep, a pipeline empowered by deep learning and a workflow manager. Evaluated on over 55,000 scans, DeepPrep demonstrates tenfold acceleration, scalability and robustness compared to the state-of-the-art pipeline, thereby meeting the scalability requirements of neuroimaging....
After the lab, you'll have the knowledge and the ability to get state-of-the-art performance in your video preprocessing workflows for your deep learning applications. Prerequisite(s): Basic familiarity with Deep Learning tools. Please disregard any reference to "Event Code"...
Bio:Hadrien Jeanis a machine learning scientist. He owns a Ph.D in cognitive science from the Ecole Normale Superieure, Paris, where he did research on auditory perception using behavioral and electrophysiological data. He previously worked in industry where he built deep learning pipelines for spe...
Segmentation Preprocessing and Deep Learning Based Classification of Skin LesionsCONVOLUTIONAL NEURAL NETWORKSIMAGE CLASSIFICATIONMELANOMASKIN LESIONMalignant melanoma is the most lethal form of skin cancer and early diagnosis and treatment are critical. Department of Dermatology data show that even in ...
Nuts-ml is a new data pre-processing library in Python for GPU-based deep learning in vision. It provides common pre-processing functions as independent, reusable units. These so called 'nuts' can be freely arranged to build data flows that are efficient
Whitening images: In the third part, we will use the tools and concepts gained in 1. and 2. to do a special kind of whitening called Zero Component Analysis (ZCA). It can be used to preprocess images for deep learning. This part will be very practical and fun ☃️!
Deep Learning Course - Level: IntermediateTensorFlow.js - Explore tensor operations through VGG16 preprocessingvideo expand_more text expand_more Exploring Tensor Operations What's up, guys? In this post, we're going to explore several tensor operations by preprocessing image data to be passed...
However, existing recognition techniques are significantly challenged by severe noise present in the original images, leading to low recognition accuracy. To address this issue, this paper proposes an oracle bone recognition method based on eigenvalue-based preprocessing and deep learning. The ...
NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems. machine-learning deep-learning gpu feature-selection nvidia recommendation-system recommender-system preprocessing...