Spain

ECAI 2020

Fully-Convolutional Intensive Feature Flow Neural Network for Text Recognition

scene text recognition; fully-convolutional intensive feature flow neural network; intensive block

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!

Multi-Stage Transfer Learning with an Application to Selection Process

Improving Supervised Superpixel-Based Codebook Representations by Local Convolutional Features

Incorporating Semantic Dependencies Extracted from Knowledge Graphs into Joint Inference template-based Information Extraction

On Measuring Inconsistency in Relational Databases with Denial Constraints

Classifying the classifier: dissecting the weight space of neural networks

Is hardness inherent in computational problems? Performance of human and electronic computers on random instances of the 0-1 knapsack problem.

A Multilayered Informative Random Walk for Attributed Social Network Embedding

Semantics of negative sequential patterns

Maximum Entropy Reinforced Single Object Visual Tracking

Preprocessing in Incomplete MaxSAT Solving

https://d3smihljt9218e.cloudfront.net/transcript/1187/subtitle/cadb0e57ee0841c850ce4ad431f9ddaa.vtt

English (automatic)

Fully-Convolutional Intensive Feature Flow Neural Network for Text Recognition

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Fully-Convolutional Intensive Feature Flow Neural Network for Text Recognition

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Next from ECAI 2020

Multi-Stage Transfer Learning with an Application to Selection Process

Similar lecture

How important are faces for person re-identification?

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PRESENTATIONS

CONFERENCES

COMPANY

RESOURCES

Downloads