Spain

ECAI 2020

Continual egocentric object recognition

open world

object recognition

continuous learning

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

technical paper

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!

ECAI 2020 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.

OpenSMax: Unknown Domain Generation Algorithm Detection

CAMUS: A Framework to Build Formal Specifications for Deep Perception Systems Using Simulators

A Neural Topical Expansion Framework for Unstructured Persona-oriented Dialogue Generation

Generative Adversarial Networks for Mitigating Biases in Machine Learning Systems

A Two-Stage Multi-Objective Deep Reinforcement Learning Framework

Online Probabilistic Interval-based Event Calculus

Saliency Detection with Deformable Convolution and Feature Attention

Non-Monotone Submodular Maximization with Multiple Knapsacks in Static and Dynamic Settings

Extended Markov Games to Learn Complex Specifications in Multi-Agent Reinforcement Learning

Efficient Neural Network Verification via Adaptive Refinement and Adversarial Search

https://d3smihljt9218e.cloudfront.net/transcript/976/subtitle/cb6ce8d1fc1c9cf478645ef17d1101b2.vtt

English (automatic)

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OpenSMax: Unknown Domain Generation Algorithm Detection

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OpenSMax: Unknown Domain Generation Algorithm Detection

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RSAC: Regularized Subspace ApproximationClassifier for Lightweight Continuous Learning

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