In this paper, we propose a self-supervised learning approach to learn meaningful and transferable representations from medical imaging video without any type... J Jiao,R Droste,L Drukker,... - IEEE 被引量: 0发表: 2020年 加载更多研究点推荐 Robust Audio Representations CLIP robust audio represen...
Audio classification is the process of analyzing and identifying any type of audio, sound, noise, musical notes, or any other similar type of data to classify them accordingly. The audio data that is available to us can occur in numerous forms, such as sound from acoustic devices, musical ch...
Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translation and Keyword Spotting. Won NAACL2022 Best Demo Award. -
Captions and a transcript can be automatically generated by Stream. PowerPoint: Turn a PowerPoint slide show into a video with narration. Or, record the desktop and either put that onto a PowerPoint slide or save it as a separate video file. Closed captio...
BasePruningMethod): PRUNING_TYPE = "unstructured" def __init__(self, threshold): self.threshold = threshold def compute_mask(self, tensor, default_mask): return torch.abs(tensor) > self.threshold prune.global_unstructured( parameters_to_prune, pruning_method=ThresholdPruning, threshold=0.01 ) ...
PINNACLEis a context-specific geometric deep learning model for generating protein representations. Leveraging single-cell transcriptomics combined with networks of protein–protein interactions, cell type-to-cell type interactions and a tissue hierarchy, PINNACLE generates high-resolution protein representations...
To retrieve an individual learning asset, given an URN, issue a GET request to the following endpoint: https复制 GET https://api.linkedin.com/v2/learningAssets/{URN} The URN types supported by this endpoint are "urn:li:lyndaCourse", "urn:li:lyndaChapter", and "urn:li:lyndaVideo". ...
Learn how deep learning works and how to use deep learning to design smart systems in a variety of applications. Resources include videos, examples, and documentation.
A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications. - NVIDIA/DALI
Each paper may be applicable to one or more types of meta-learning frameworks, including optimization-based and metric-based, and may be applicable to multiple data sources, including image, text, audio, video, and multi-modality.These are marked in the type column. In addition, for different...