DeText: LinkedIn’s Open Source Deep Learning Framework for Natural Language Processing
Join Your Own Private LoRa Mesh Network
🎉 It is time! #Mastodon 3.2.0 is here! What's in it? Have a look:
Episode 2: The impact of machines that "learn" and produce https://fossandcrafts.org/episodes/2-machine-learning-impact.html
Discussion about recent developments in machine learning and the impact they could have on FOSS, programming in general, art production, and civic society
New episode of @fossandcrafts out! @mlemweb and I break down some ways we could see machine learning advancements impacting our work, also seen through a historical lens of other automation/technical advancements https://fossandcrafts.org/episodes/2-machine-learning-impact.html
Announcing .NET 5.0 Preview 7
AutoCount: Unsupervised Segmentation and Counting of Organs in Field Images. (arXiv:2007.09178v1 [cs.CV]) http://arxiv.org/abs/2007.09178
Can we Estimate Truck Accident Risk from Telemetric Data using Machine Learning?. (arXiv:2007.09167v1 [cs.LG]) http://arxiv.org/abs/2007.09167
Improving Object Detection with Selective Self-supervised Self-training. (arXiv:2007.09162v1 [cs.CV]) http://arxiv.org/abs/2007.09162
Tutorial: Train a Deep Learning Model in PyTorch and Export It to ONNX
Tend Your Garden… Again
Ham Radio Mobile Operations Circa 1919
Privacy Preserving Text Recognition with Gradient-Boosting for Federated Learning. (arXiv:2007.07296v1 [cs.CV]) http://arxiv.org/abs/2007.07296
Adversarial learning for product recommendation. (arXiv:2007.07269v1 [cs.IR]) http://arxiv.org/abs/2007.07269
Image De-Quantization Using Generative Models as Priors. (arXiv:2007.07923v1 [cs.CV]) http://arxiv.org/abs/2007.07923
How Early Radio Receivers Worked
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