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Estimating the Number of Receiving Nodes in 802.11 Networks via Machine Learning Techniques.

, , , и . GLOBECOM, стр. 1-7. IEEE, (2016)

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Matteo Rini

Matteo Garavoglia

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Application of I-COMO device towards geographic disease enrichment pattern revealed from electronic medical record at a large Urban academic medical center., , и . PervasiveHealth, стр. 282-287. ACM, (2017)Estimating the Number of Receiving Nodes in 802.11 Networks via Machine Learning Techniques., , , и . GLOBECOM, стр. 1-7. IEEE, (2016)Applying Machine Learning Techniques to a Real Cognitive Network: File Transfer ETAs Prediction., , и . GLOBECOM, стр. 1-7. IEEE, (2015)Satellite images and machine learning can identify remote communities to facilitate access to health services., , , , , , , , , и . J. Am. Medical Informatics Assoc., 26 (8-9): 806-812 (2019)Automatic processing of Electronic Medical Records using Deep Learning., , , , , и . PervasiveHealth, стр. 251-257. ACM, (2018)Deep Representation Learning of Electronic Health Records to Unlock Patient Stratification at Scale., , , , , , , , и . CoRR, (2020)Improving Internet of Things communications through compression and classification., , и . PerCom Workshops, стр. 284-289. IEEE Computer Society, (2012)Discovery, Localization and Recognition of Smart Objects by a Mobile Robot., , , , , , и . SIMPAR, том 6472 из Lecture Notes in Computer Science, стр. 436-448. Springer, (2010)On the Exploitation of the Android OS for the Design of a Wireless Mesh Network Testbed., , , и . MILCOM, стр. 1032-1038. IEEE, (2013)Scaling Structural Learning with NO-BEARS to Infer Causal Transcriptome Networks., , , , и . PSB, стр. 391-402. (2020)