Hi Samia, I have uploaded the ppt with audio embedded https://drive.google.com/drive/folders/1-7BhpfaoK5feK3p43d_Stp4JvMcGuG3b?usp=sharing
regards Dr. Mohsen Ali | Assistant Professor Information Technology University (ITU) 346-B, Ferozepur Road, Lahore, Pakistan E-mail: mohsen....@itu.edu.pk | Phone: +92 (42) 9904 6049 Website: Mohsen Ali <http://itu.edu.pk/faculty-itu/mohsen-ali/> | Google Scholar: https://goo.gl/WzLVj9 On Thu, Mar 5, 2020 at 5:42 AM Samia Ibtasam <sam...@cs.washington.edu> wrote: > Hi everyone, > Join us for the Change seminar tomorrow at 12:30 pm. In case you cannot > attend in person, we will also live-stream the talk using the link > https://youtu.be/4WVRKpvlFgs > > Best, > Samia Ibtasam <http://samiaibtasam.com/> > PhD Student > Paul G. Allen School of Computer Science & Engineering > University of Washington > > > > On Mon, Mar 2, 2020 at 10:03 AM Samia Ibtasam <sam...@cs.washington.edu> > wrote: > >> Hi everyone, >> >> Please note that this week's special Change seminar will be on Thursday, >> March 5th, 2020 starting at 12:30 pm. Please note the change in day and >> time only for this week. There won't be a seminar on Tuesday this week. >> >> >> *When: *Thursday 3/5, 12:30 pm-1:30 pm >> >> *Where:* CSE1 305 (Allen Building) >> >> *Who:* Dr. Mohsen Ali (Intelligent Machines Lab, Information Technology >> University, Pakistan) >> >> *Title:* Deep Learning for Intelligent Mapping of Pakistan >> >> >> *Abstract * >> >> The past decade saw the graduation of machine learning from the academic >> setting to incorporation into the practical world. From self-driving cars >> to designing antibiotics, from personal life to businesses we are relying >> on the data-driven algorithms to make decisions for us. Dependence on the >> data means that members of societies, which are not similar to the >> technologically advanced ones, and which do not produce a regular and >> uniform stream of data, are left behind. With a data democratization a >> target, we are trying to fill the gap by designing deep learning-based >> neural networks for satellite imagery to do urban analysis and combine the >> information extracted from it with the existing geospatial data sources to >> create rich informative maps of Pakistan in the public domain. >> >> >> >> In this talk, I will start by looking at an attention-based deep neural >> network we designed to compute the fine-grain building foot-print map of >> the province Punjab in Pakistan. Moving from there, I will talk about our >> work on counting buildings from satellite imagery (think about boxes inside >> boxes, next to the other boxes) and detecting areas devastated by war or >> natural disaster. All this will lead to the Slum Detection project and how >> we boot-strapped our algorithm to detect slums from satellite imagery in >> three cities of Pakistan. And our current effort to use satellite imagery >> and other GIS information to approximate multidimensional poverty. Finally, >> I will introduce two on-going projects Tag-Pakistan and “Yadain: An Oral >> History”; [Yadain means memories in Urdu] where we are using crowdsourced >> images and augmented reality to create highly informative maps. >> >> >> >> >> >> *Bio:* >> >> Mohsen Ali is an Assistant Professor >> <http://itu.edu.pk/faculty-itu/mohsen-ali/> at Information Technology >> University and co-founder of the Intelligent Machines Lab >> <http://im.itu.edu.pk/researches/>. IML has been established with the >> objective to provide a platform for researchers and engineers working in >> machine learning, computer vision, and robotics to collaborate and solve >> real-world problems. Mohsen’s current interest lies in theoretical and >> practical problems entailing Computer Vision and Machine Learning >> (including Deep learning), and their application in the field of video and >> image analysis, remote sensing and affective computing >> <http://im.itu.edu.pk/research/affective-computing/>. His work on >> decreasing the Affective Gap, between the multimedia content and modeling >> emotional response, and designing Emotion Filters >> <http://im.itu.edu.pk/affective-image-transfer/> to transform an image >> in order to garner desired emotional impact, has been accepted in respected >> computer vision conferences. >> >> >> Currently, he is working on satellite imagery analysis using deep >> learning to understand urbanization and economic condition. In >> collaboration with UNDP and Sustainable Development Goal Tech Lab at ITU, >> he is working to replace intensive surveying exercises to detect and >> estimate the economic condition of slums, with satellite imagery and >> geospatial data analysis techniques. His work on counting buildings >> <http://im.itu.edu.pk/deepcount/> and detecting destroyed areas from >> satellite imagery has been accepted in a top-ranking journal. Intending to >> democratize the data, he is interested in using machine learning and >> computer vision to collect large datasets capturing bio-diversity, culture, >> and history to create an informative, self-growing and in-depth map of >> Pakistan. His group is exploring techniques like active learning, domain >> adaptation, unsupervised learning for the task. >> >> >> Mohsen Ali completed his doctoral studies from the University of Florida >> in the area of Computer Vision and is the recipient of the Fulbright >> Scholarship award. His work has been accepted in venues like ICCV, CVPR, >> ISPRS P&RS. >> >> Our Research Page: Computer Vision and Machine Learning Research Group >> <http://im.itu.edu.pk/computer-vision-and-machine-learning-research-group/> >> >> Selected Publications: http://im.itu.edu.pk/publications/ >> >> Google Scholar Page: https://scholar.google.com.pk/ >> <https://scholar.google.com.pk/citations?user=59ISSCEAAAAJ&hl=en> >> >> Best, >> Samia Ibtasam <http://samiaibtasam.com/> >> Ph.D. Student >> Paul G. Allen School of Computer Science & Engineering >> University of Washington >> >> _______________________________________________ > change mailing list > change@change.washington.edu > https://changemm.cs.washington.edu/mailman/listinfo/change >
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