Spain

ECAI 2020

Weak Supervision helps Emergence of Word-Object Alignment and improves Vision-Language Tasks

visual question answering

vision and language

deep learning

ECAI2020 featured a full programme of technical papers, as well as many AI-related events of interest for researchers, students and all attendants who are interested on contemporary AI, including:




**An extensive programme of workshops, tutorials, and invited speakers**

**The Prestigious Applications of Intelligent Systems conference (PAIS)**

**The Frontiers in AI track sessions**

**The Lab To Market event**

**The Women in AI time**

**The EU Challenges forum**

… and many more!

ICPR 2020 is the premier international conference on Pattern Recognition, gathering leading researchers from around the world to present their latest achievements in Pattern Analysis and Recognition, applied Artificial Intelligence and Machine Learning. The topic of the year is " Putting Artificial intelligence to work on Patterns". 
For the first time, ICPR has employed a two-round review process similar to journal submissions, with new papers allowed to be submitted in either the first or second round and papers submitted in the first round and not accepted allowed to be revised and re-submitted for second round review. 

In this edition of the **ICPR 2020** Conference, there are 1407 Oral/Poster presentations organized in five Tracks: 
- Artificial Intelligence, Machine Learning for Pattern Analysis; 
- Biometrics, Human Analysis and Behavior Understanding; Computer Vision, Robotics and Intelligent Systems; 
- Document and Media Analysis; and 
- Image and Signal Processing. 

The **ICPR 2020** Main Conference program also includes 7 Keynotes from prominent world-renowned scientists, 8 Tutorials, 28 Demos, 8 Challenges, 2 Panels, as well as an Industry/Sponsor Exhibition. In addition, 41 Workshops on a range of important current and emerging research topics complete the ICPR 2020 program. 


ICPR 2020 MAIN CONFERENCE

technical paper

Election Score Can Be Harder Than Winner

Retrospective and Prospective Mixture-of-Generators for Task-oriented Dialogue Response Generation

Derivative-Free Optimization with Adaptive Experience for Efficient Hyper-Parameter Tuning

Uniform State Abstraction For Reinforcement Learning

A Lagrangian Approach to Information Propagation in Graph Neural Networks

A Compact Spectral Descriptor for Shape Deformations

Coulomb Autoencoders

A Knowledge-based System for the Dynamic Generation and Classification of Novel Contents in Multimedia Broadcasting

SETNet : A Novel Semi-Supervised Approach for Semantic Parsing

A Knowledge-driven Approach to Explaining Black-box Models

Weak Supervision helps Emergence of Word-Object Alignment and improves Vision-Language Tasks

Next from ECAI 2020

Election Score Can Be Harder Than Winner

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