All Outputs (5)

A classification-regression deep learning model for people counting (2018)
Conference Proceeding
Xu, B., Zou, W., Garibaldi, J., & Qiu, G. (2018). A classification-regression deep learning model for people counting. In K. Arai, S. Kapoor, & R. Bhatia (Eds.), Intelligent Systems and Applications Proceedings of the 2018 Intelligent Systems Conference (IntelliSys) Volume 1 (136-149). https://doi.org/10.1007/978-3-030-01054-6_9

In this paper, we construct a multi-task deep learning model to simultaneously predict people number and the level of crowd density. Motivated by the success of applying " ambiguous labelling " to age estimation problem, we also manage to employ this... Read More about A classification-regression deep learning model for people counting.

Direct Application of Convolutional Neural Network Features to Image Quality Assessment (2018)
Conference Proceeding
Hou, X., Sun, K., Liu, B., Gong, Y., Garibaldi, J., & Qiu, G. (2018). Direct Application of Convolutional Neural Network Features to Image Quality Assessment. In 2018 IEEE Visual Communications and Image Processing (VCIP). https://doi.org/10.1109/VCIP.2018.8698726

© 2018 IEEE. We take advantage of the popularity of deep con-volutional neural networks (CNNs) and have developed a very simple image quality assessment method that rivals state of the art. We show that convolutional layer outputs (deep features) of... Read More about Direct Application of Convolutional Neural Network Features to Image Quality Assessment.

Visual landmark sequence-based indoor localization (2017)
Conference Proceeding
Li, Q., Zhu, J., Liu, T., Garibaldi, J., Li, Q., & Qiu, G. (2017). Visual landmark sequence-based indoor localization. In Proceedings of the 1st Workshop on Artificial Intelligence and Deep Learning for Geographic Knowledge Discovery - GeoAI '17 (14-23). https://doi.org/10.1145/3149808.3149812

This paper presents a method that uses common objects as landmarks for smartphone-based indoor localization and navigation. First, a topological map marking relative positions of common objects such as doors, stairs and toilets is generated from floo... Read More about Visual landmark sequence-based indoor localization.

Crowd-sourcing Applied to Photograph-Based Automatic Habitat Classification (2014)
Conference Proceeding
Torres Torres, M., & Qiu, G. (2014). Crowd-sourcing Applied to Photograph-Based Automatic Habitat Classification. In MAED '14: Proceedings of the 3rd ACM International Workshop on Multimedia Analysis for Ecological Data, 19-24. doi:10.1145/2661821.2661824

Habitat classification is a crucial activity for monitoring environmental biodiversity. To date, manual methods, which are laborious, time-consuming and expensive, remain the most successful alternative. Most automatic methods use remote-sensed image... Read More about Crowd-sourcing Applied to Photograph-Based Automatic Habitat Classification.

Supervised learning and anti-learning of colorectal cancer classes and survival rates from cellular biology parameters
Conference Proceeding
Roadknight, C., Aickelin, U., Qiu, G., Scholefield, J., & Durrant, L. Supervised learning and anti-learning of colorectal cancer classes and survival rates from cellular biology parameters.

In this paper, we describe a dataset relating to cellular and physical conditions of patients who are operated upon to remove colorectal tumours. This data provides a unique insight into immunological status at the point of tumour removal,tumour cl... Read More about Supervised learning and anti-learning of colorectal cancer classes and survival rates from cellular biology parameters.