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Training of both approaches was done using a machine equipped with a single NVIDIA GTX Titan X (Pascal 12 GB) with MATLAB <t> R2018b. </t> Testing was done on a notebook, namely, a Lenovo ThinkPad W540 (CPU i7-4710MQ @ 2.50 GHz, 8 GB RAM, NVIDIA Quadro K1100M) with MATLAB <t> R2018b. </t>
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Training of both approaches was done using a machine equipped with a single NVIDIA GTX Titan X (Pascal 12 GB) with MATLAB <t> R2018b. </t> Testing was done on a notebook, namely, a Lenovo ThinkPad W540 (CPU i7-4710MQ @ 2.50 GHz, 8 GB RAM, NVIDIA Quadro K1100M) with MATLAB <t> R2018b. </t>
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Training of both approaches was done using a machine equipped with a single NVIDIA GTX Titan X (Pascal 12 GB) with MATLAB <t> R2018b. </t> Testing was done on a notebook, namely, a Lenovo ThinkPad W540 (CPU i7-4710MQ @ 2.50 GHz, 8 GB RAM, NVIDIA Quadro K1100M) with MATLAB <t> R2018b. </t>
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Image Search Results


Training of both approaches was done using a machine equipped with a single NVIDIA GTX Titan X (Pascal 12 GB) with MATLAB  R2018b.  Testing was done on a notebook, namely, a Lenovo ThinkPad W540 (CPU i7-4710MQ @ 2.50 GHz, 8 GB RAM, NVIDIA Quadro K1100M) with MATLAB  R2018b.

Journal: Sensors (Basel, Switzerland)

Article Title: Time Coherent Full-Body Poses Estimated Using Only Five Inertial Sensors: Deep versus Shallow Learning

doi: 10.3390/s19173716

Figure Lengend Snippet: Training of both approaches was done using a machine equipped with a single NVIDIA GTX Titan X (Pascal 12 GB) with MATLAB R2018b. Testing was done on a notebook, namely, a Lenovo ThinkPad W540 (CPU i7-4710MQ @ 2.50 GHz, 8 GB RAM, NVIDIA Quadro K1100M) with MATLAB R2018b.

Article Snippet: The chosen input sequence configuration (2 future poses) results in a delay of 67 ms using MATLAB R2018b (MathWorks, Inc., Natick, MA, USA).

Techniques: