This dataset features a unique combination of half-meter quad-polarized X-band SAR imagery (Figure ) and half-meter optical imagery over the port of Rotterdam, the Netherlands. We envision our multi-year datasets can support the ML community in developing generalizable longitudinal behavior modeling algorithms. the Multi-Sensor All Weather Mapping (MSAW) dataset. ![]() Our results indicate that both prior depression detection algorithms and domain generalization techniques show potential but need further research to achieve adequate cross-dataset generalizability. As a starting point, we provide the benchmark results of 18 algorithms on the task of depression detection. ![]() Our datasets can support multiple cross-dataset evaluations of behavior modeling algorithms’ generalizability across different users and years. We present the first multi-year passive sensing datasets, containing over 700 user-years and 497 unique users’ data collected from mobile and wearable sensors, together with a wide range of well-being metrics. Moreover, prior studies mainly evaluate algorithms using data from a single population within a short period, without measuring the cross-dataset generalizability of these algorithms. ![]() However, there is a lack of a comprehensive public dataset that serves as an open testbed for fair comparison among algorithms. Abstract: Recent research has demonstrated the capability of behavior signals captured by smartphones and wearables for longitudinal behavior modeling.
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