DEEP LEARNiNG WITH MULTIPLE DATA TYPES

HYBRID NEURAL NETWORK ARCHITECTURES

Full-day Workshop

2019 EVENTS

This workshop explores how convolutional and recurrent neural networks can be combined to generate effective descriptions of content within images and video clips.

Learn how to train a network using TensorFlow and the Microsoft Common Objects in Context (COCO) dataset to generate captions from images and video by:

  • Implementing deep learning workflows like image segmentation and text generation
  • Comparing and contrasting data types, workflows, and frameworks
  • Combining computer vision and natural language processing

Upon completion, you’ll be able to solve deep learning problems that require multiple types of data inputs.

Instructors

Luigi Troiano (troiano@unisannio.it)

Piero Altoé (paltoe@nvidia.com)

Elena Mejuto Villa (mejutovilla@unisannio.it)

SEP

18

10h00

University of Salerno

Dip. Scienze Aziendali, Management e Innovation Systems (DISA-MIS)

Laboratorio Multimediale

Building B2

84084 Campus di Fisciano (Italy)

FEB

05

09h00

University of Ferrara

Department of Physics and Earth Sciences

Via G. Saragat 1

44122 Ferrara (Italy)