Climate Change/Environmental

This dataset is in support of my 2 research papers - 'Short Circuit Analysis of 72Ah Li-Ion BMC - Part I' and 'Short Circuit Analysis of 72Ah Li-Ion BMC - Part II'.

 Faults and datasets can be copied to submit in fire cause investigation reports or thesis. 

This dataset is a collection of data of battery and BMC  faults. 

The SWINSEG dataset contains 115 nighttime images of sky/cloud patches along with their corresponding binary ground truth maps The ground truth annotation was done in consultation with experts from Singapore Meteorological Services. All images were captured in Singapore using WAHRSIS, a calibrated ground-based whole sky imager, over a period of 12 months from January to December 2016. All image patches are 500x500 pixels in size, and were selected considering several factors such as time of the image capture, cloud coverage, and seasonal variations.

We have labeled 683 images and 2015 bounding boxes in total for now. We used 80% of the dataset which are 546 images for training and the rest of 20% which are 137 images for evaluation, and all images in the dataset have the same resolution at 1920*1080. Table.I summaries the statistics of the dataset, the category of floating leaves region has the most bounding box labels and the category of floating weeds region has the largest average size of bounding boxes.

Emergency  managers  of  today  grapple  with  post-hurricane damage assessment that is often labor-intensive, slow,costly,   and   error-prone.   As   an   important   first   step   towards addressing  the   challenge,   this   paper   presents   the   development of  benchmark  datasets  to  enable  the  automatic  detection  ofdamaged buildings from post-hurricane remote sensing imagerytaken  from  both  airborne  and  satellite  sensors.  Our  work  has two  major  contributions:  (1)  we  propose  a  scalable  framework to  create  benchmark  datasets  of  hurricane-damaged  buildings