Deep Image Prior [paper] [article] [code] Online Deep Learning: Learning Deep Neural Networks on the Fly [arXiv] Learning Explanatory Rules from Noisy Data [arXiv] Improving Palliative Care with Deep Learning [arXiv] [article] VoxelNet: End-to-End Learning for Point Cloud Based 3D Object ...
DeepSpeedenabled the world's most powerful language models (at the time of this writing) such asMT-530BandBLOOM. It is an easy-to-use deep learning optimization software suite that powers unprecedented scale and speed for both training and inference. With DeepSpeed you can: ...
We note that in their paper, they describe using high-field MR data and images to train their neural network as well. In conclusion, the main contribution of this paper is that our results show that deep learning-based methods have the potential to tackle another problem in the field of ...
The desire to understand how the brain generates and patterns behavior has driven rapid methodological innovation in tools to quantify natural animal behavior. While advances in deep learning and computer vision have enabled markerless pose estimation in
\quad 2. 为了优化新提出的退化模型(degradation model)引发的能量函数(energy function),故他们用一些数学方法(i.e. variable splitting technique)导出了即插即用算法(plug-and-play algorithm)以优化引发的能量函数,同时,即插即用算法(plug-and-play algorithm)可以把超分先验(super-resolver prior)而非去噪先验...
We discuss the computational approaches (CPU, GPU, FPGA) by comparing the influence of each tool on deep learning algorithms. The rest of the paper is organized as follows: “Survey methodology” section describes The survey methodology. “Background” section presents the background. “Classificati...
it also poses some challenges on deep learning. Therefore, in the past few years, many deep learning models have been developed for big data learning. In this paper, we provide a survey of big data deep learning models.Big datais typically defined by the four V’s model: volume, variety...
This shift demands a structured analysis and revision of the current status on the research domain of deep learning-based semantic segmentation. The focus of this paper is on urban remote sensing images. We review and perform a meta-analysis to juxtapose recent papers in terms of research ...
In this paper, we present a new method for multitask learning applied to ultrasound beamforming. Beamforming is a critical component in the ultrasound image formation pipeline. Ultrasound images are constructed using sensor readings from multiple transducer elements, with each element typically capturing...
The variables epochs and mini_batch_size are what you'd expect - the number of epochs to train for, and the size of the mini-batches to use when sampling. eta is the learning rate, ηη. If the optional argument test_data is supplied, then the program will evaluate the network after...