Code and dataset for IEEE TKDE paper "Dynamic Heterogeneous Information Network Embedding with Meta-path based Proximity" - rootlu/DyHNE
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Dynamic scales of input for training with multiple GPUs For the task of semantic segmentation, it is good to keep aspect ratio of images during training. So we re-implement theDataParallelmodule, and make it support distributing data to multiple GPUs in python dict, so that each gpu can proce...
In addition to deep learning model, there is a new large video dataset of echocardiograms for computer vision research.Below figures are representative frames from the EchoNet-Dynamic dataset. Eleven frames of five independent videos are shown after pre-processing removing ECG data, text labels, ...
Objectives: Recognition of mobile applications within encrypted network traffic holds considerable effects across multiple domains, encompassing network administration, security, and digital marketing. The creation of network traffic classifiers capable of adjusting to dynamic and unforeseeable real-world settings...
The INTERACTION dataset contains naturalistic motions of various traffic participants in a variety of highly interactive driving scenarios from different countries. The dataset can serve for many behavior-related research areas, such as 1) intention/b
(for example, only humans recursively combine linguistic elements into complex, hierarchical expressions with long-range dependencies3,4). Language is also very dynamic and contextualized. Linguistic narratives evolve over time: the meaning of any given element depends in part on the history of ...
Despite these limitations, Sentinel2GlobalLULC remains to our knowledge the first global LULC mapping dataset that includes up to 29 LULC classes, a number much higher than the valuable Dynamic World dataset55, which only provides 9 LULC classes yet. ...