All Outputs (5)

Food places classification in egocentric images using Siamese neural networks. (2019)
Conference Proceeding
SARKER, M.M.K., BANU, S.F., RASHWAN, H.A., ABDEL-NASSER, M., SINGH, V.K., CHAMBON, S., RADEVA, P. and PUIG, D. 2019. Food places classification in egocentric images using Siamese neural networks. In Sabater-Mir, J., Torra, V., Aguiló, I. and González-Hidalgo, M. (eds.) Artificial intelligence research and development: proceedings of the 22nd International conference of the Catalan Association for Artificial Intelligence (CCIA 2019), 23-25 October 2019, Colònia de Sant Jordi, Spain. Frontiers in artificial intelligence and applications, 319. Amsterdam: IOS Press [online], pages 145-151. Available from: https://doi.org/10.3233/FAIA190117

Wearable cameras have become more popular in recent years for capturing unscripted moments in the first-person, which help in analysis of the user's lifestyle. In this work, we aim to identify the daily food patterns of a person through recognition o... Read More about Food places classification in egocentric images using Siamese neural networks..

Breast tumor segmentation and shape classification in mammograms using generative adversarial and convolutional neural network. (2019)
Journal Article
SINGH, V.K., RASHWAN, H.A., ROMANI, S., AKRAM, F., PANDEY, N., SARKER, M.M.K., SALEH, A., ARENAS, M., ARQUEZ, M., PUIG, D. and TORRENTS-BARRENA, J. 2020. Breast tumor segmentation and shape classification in mammograms using generative adversarial and convolutional neural network. Expert systems with applications [online], 139, article number 112855. Available from: https://doi.org/10.1016/j.eswa.2019.112855

Mammogram inspection in search of breast tumors is a tough assignment that radiologists must carry out frequently. Therefore, image analysis methods are needed for the detection and delineation of breast tumors, which portray crucial morphological in... Read More about Breast tumor segmentation and shape classification in mammograms using generative adversarial and convolutional neural network..

Hierarchical approach to classify food scenes in egocentric photo-streams. (2019)
Journal Article
MARTINEZ, E.T., LEYVA-VALLINA, M., SARKER, M.M.K., PUIG, D., PETKOV, N. and RADEVA, P. 2020. Hierarchical approach to classify food scenes in egocentric photo-streams. IEEE journal of biomedical and health informatics [online], 24(3), pages 866-877. Available from: https://doi.org/10.1109/JBHI.2019.2922390

Recent studies have shown that the environment where people eat can affect their nutritional behavior. In this paper, we provide automatic tools for personalized analysis of a person's health habits by the examination of daily recorded egocentric pho... Read More about Hierarchical approach to classify food scenes in egocentric photo-streams..

Recognizing food places in egocentric photo-streams using multi-scale atrous convolutional networks and self-attention mechanism. (2019)
Journal Article
SARKER, M.M.K., RASHWAN, H.A., AKRAM, F., TALAVERA, E., BANU, S.F., RADEVA, P. and PUIG, D. 2019. Recognizing food places in egocentric photo-streams using multi-scale atrous convolutional networks and self-attention mechanism. IEEE access [online], 7, pages 39069-39082. Available from: https://doi.org/10.1109/ACCESS.2019.2902225

Wearable sensors (e.g., lifelogging cameras) represent very useful tools to monitor people's daily habits and lifestyle. Wearable cameras are able to continuously capture different moments of the day of their wearers, their environment, and interacti... Read More about Recognizing food places in egocentric photo-streams using multi-scale atrous convolutional networks and self-attention mechanism..

FinSeg: finger parts semantic segmentation using multi-scale feature maps aggregation of FCN. (2019)
Conference Proceeding
SALEH, A., RASHWAN, H., ABDEL-NASSER, M., SINGH, V., ABDULWAHAB, S., SARKER, M., GARCIA, M. and PUIG, D. 2019. FinSeg: finger parts semantic segmentation using multi-scale feature maps aggregation of FCN. In Tremeau, A., Farinella, G.M. and Braz, J. (eds.). Proceedings of 14th international joint conferences on Computer vision, imaging and computer graphics theory and applications 2019 (VISIGRAPP 2019), 25-27 February 2019, Prague, Czech Republic. Setúbal, Portugal: SciTePress [online], 5, pages 77-84. Available from: https://doi.org/10.5220/0007382100770084

Image semantic segmentation is in the center of interest for computer vision researchers. Indeed, huge number of applications requires efficient segmentation performance, such as activity recognition, navigation, and human body parsing, etc. One of t... Read More about FinSeg: finger parts semantic segmentation using multi-scale feature maps aggregation of FCN..