deep learningechoemergency medicineemergency ultrasoundpoint‐of‐care ultrasoundLittle is known about optimal deep learning (DL) approaches for point-of-care ultrasound (POCUS) applications. We compared 6 popu
we chose the architecture with the highest AUC in the internal validation set and used that model to report performance for that view in all subsequent experiments (a summary of the architectures chosen for each view is shown in Supplementary Table 8, and an example for the PL DEEP view is ...
Dynamic Graphs: PyTorch allows developers to create dynamic graphs on-the-fly, enabling them to quickly prototype and iterate on new models and architectures. Auto-differentiation: PyTorch model allows developers to easily calculate gradients and perform backpropagation with its automatic differentiation ca...
最近在arxiv看到了一篇有意思的文章,标题是torch.manual seed(3407) is all you need: On the influence of random seeds in deep learning architectures for computer vision。不得不吐槽一下,最近很多论文标题都是"XX is all you need",似乎只要标题足够吸引眼球就能提高被录用的几率。但显然,这一trick是有效...
Also, supervised deep learning models are very data hungry and therefore rely on large amounts of training data to perform well. In this paper, we present a multi-task learning approach for segmentation and classification of nuclei, glands, lumina and different tissue regions that leverages data ...
Architectures for AI Factories NVIDIA Blackwell GPU Architecture The NVIDIA Blackwell architecture defines the next chapter in generative AI and accelerated computing with unparalleled performance, efficiency, and scale. NVIDIA Blackwell features six transformative technologies that unlock breakthroughs in data ...
neon is Intel's reference deep learning framework committed to best performance on all hardware. Designed for ease-of-use and extensibility. Tutorials and iPython notebooks to get users started with using neon for deep learning. Support for commonly used layers: convolution, RNN, LSTM, GRU, Batch...
“Consciousness is no longer something mysterious and magical,” explains Kanai, a neuroscientist. “We are seeing AI researchers getting closer to architectures relevant to consciousness.” He believes big advances in these areas are the key to the future of AI. ...
We conducted this investigation via an extensive empirical study that involves multiple learning sources, as well as multiple deep learning architectures with varying levels of information sharing between sources, in order to learn music representations. We then validate these representations considering ...
Deep Reinforcement Learning with Double Q-Learning : [Paper][Code] Dueling Network Architectures for Deep Reinforcement Learning : [Paper][Code] Applications Image Recognition Deep Residual Learning for Image Recognition : [Paper][Code] Very Deep Convolutional Networks for Large-Scale Image Recognition ...