Upcoming MATLAB and Simulink Webinars

Demystifying Deep Learning: Semantic Segmentation and Deployment


Deep learning can achieve state-of-the-art accuracy for many tasks considered algorithmically unsolvable using traditional machine learning, including classifying objects in a scene or recognizing optimal paths in an environment. In this webinar, we’ll decipher practical knowledge of the domain of deep learning, and demonstrate new MATLAB features that simplify these tasks and eliminate the low-level programming. From prototype to production: we’ll build and train neural networks, and discuss automatically converting a model to CUDA to run natively on GPUs.

Note: This webinar builds on concepts previously discussed in the Deep Learning for Computer Vision webinar.


  • Perform pixel-level semantic segmentation on images
  • Import and use pre-trained models from TensorFlow and Caffe
  • Speed up network training with parallel computing on a cluster
  • Use data augmentation to increase the accuracy of a deep learning model
  • Automatically convert a model to CUDA to run on GPUs

Please allow approximately 45 minutes to attend the presentation and Q&A session. We will be recording this webinar, so if you can't make it for the live broadcast, register and we will send you a link to watch it on-demand.

About the Presenter

Abhijit Bhattacharjee is a Senior Application Engineer at MathWorks, specializing in the areas of computer vision, audio signal processing, and machine learning. Prior to MathWorks, Abhijit was a researcher at USC Information Sciences Institute, working in programs funded by NASA and DARPA. Projects included hyperspectral image processing and audio steganography. He holds an M.S.E.E. degree from the University of Southern California and works with clients in all industries, including consumer devices, semiconductors, government, and academic.

Pitambar Dayal is a Technical Marketing Manager for MathWorks Image Processing and Computer Vision products. Prior to MathWorks, Pitambar earned his B.S. studying Biomedical Engineering at NJIT and working in a brain-imaging lab, where he researched fMRI patterns in ischemic stroke patients (using MATLAB, of course). Outside of work, Pitambar spends his time traveling, watching basketball, and playing ultimate frisbee. His favorite food is Margherita Pizza and his favorite dessert is Belgian waffles.

Product Focus

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