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TransSLC: skin lesion classification in dermatoscopic images using transformers. (2022)
Conference Proceeding
SARKER, M.M.K., MORENO-GARCÍA, C.F., REN, J. and ELYAN, E. 2022. TransSLC: skin lesion classification in dermatoscopic images using transformers. In Yang, G., Aviles-Rivero, A., Roberts, M. and Schönlieb, C.-B. (eds.) Medical image understanding and analysis: proceedings of 26th Medical image understanding and analysis 2022 (MIUA 2022), 27-29 July 2022, Cambridge, UK. Lecture notes in computer sciences, 13413. Cham: Springer [online], pages 651-660. Available from: https://doi.org/10.1007/978-3-031-12053-4_48

Early diagnosis and treatment of skin cancer can reduce patients' fatality rates significantly. In the area of computer-aided diagnosis (CAD), the Convolutional Neural Network (CNN) has been widely used for image classification, segmentation, and rec... Read More about TransSLC: skin lesion classification in dermatoscopic images using transformers..

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..

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..

Brain MR image segmentation using multiphase active contours based on local and global fitted images. (2018)
Conference Proceeding
AKRAM, F., SINGH, V.K., SARKER, M.M.K., GARCIA, M.A. and PUIG, D. 2018. Brain MR image segmentation using multiphase active contours based on local and global fitter images. In Falomir, Z., Gilbert, K. and Plaza, E. (eds.). Artificial intelligence research and development: current challenges, new trends and applications; contributions from 21st international conference of Catalan Association for Artificial Intelligence 2018 (CCIA 2018), 8-10 October 2018, Alt Empordà, Spain. Frontiers in artificial intelligence and applications, 308. Amsterdam: IOP Press [online], pages 325-334. Available from: https://doi.org/10.3233/978-1-61499-918-8-325

The study of white matter (WM), grey matter (GM) and cerebrospinal fluid (CSF) regions in the brain magnetic resonance (MR) images can be useful for determining different brain disorders, assisting brain surgery, post-surgical analysis, saliency dete... Read More about Brain MR image segmentation using multiphase active contours based on local and global fitted images..

SLSDeep: Skin Lesion Segmentation Based on Dilated Residual and Pyramid Pooling Networks (2018)
Conference Proceeding
SARKER, M.M.K., RASHWAN, H.A., AKRAM, F., BANU, S.F., SALEH, A., SINGH, V.K., CHOWDHURY, F.U.H., ABDULWAHAB, S., ROMANI, S., RADEVA, P. and PUIG, D. 2018. SLSDeep: skin lesion segmentation based on dilated residual and pyramid pooling networks. In Frangi, A.F., Schnabel, J.A., Davatzikos, C., Alberola-López, C. and Fictinger, G. (eds.) Medical image computing and computer assisted intervention (MICCAI 2018): proceedings of 21st international conference on Medical image computing and computer assisted interventions 2018 (MICCAI 2018), 16-20 September 2018, Granada, Spain. Lecture notes in computer science, 11071. Cham: Springer [online], pages 21-29. Available from: https://doi.org/10.1007/978-3-030-00934-2_3

Skin lesion segmentation (SLS) in dermoscopic images is a crucial task for automated diagnosis of melanoma. In this paper, we present a robust deep learning SLS model represented as an encoder-decoder network. The encoder network is constructed by di... Read More about SLSDeep: Skin Lesion Segmentation Based on Dilated Residual and Pyramid Pooling Networks.

Conditional generative adversarial and convolutional networks for X-ray breast mass segmentation and shape classification. (2018)
Conference Proceeding
SINGH, V.K., ROMANI, S., RASHWAN, H.A., AKRAM, F., PANDEY, N., SARKER, M.M.K., ABDULWAHAB, S., TORRENTS-BARRENA, J., SALEH, A., ARQUEZ, M., ARENAS, M. and PUIG, D. 2018. Conditional generative adversarial and convolutional networks for X-ray breast mass segmentation and shape classification. In Frangi, A.F., Schnabel, J.A., Davatzikos, C., Alberola-López, C. and Fictinger, G. (eds.) Medical image computing and computer assisted intervention (MICCAI 2018): proceedings of 21st international conference on Medical image computing and computer assisted interventions 2018 (MICCAI 2018), 16-20 September 2018, Granada, Spain. Lecture notes in computer science, 11071. Cham: Springer [online], pages 833-840. Available from: https://doi.org/10.1007/978-3-030-00934-2_92

This paper proposes a novel approach based on conditional Generative Adversarial Networks (cGAN) for breast mass segmentation in mammography. We hypothesized that the cGAN structure is well-suited to accurately outline the mass area, especially when... Read More about Conditional generative adversarial and convolutional networks for X-ray breast mass segmentation and shape classification..

Deep visual embedding for image classification. (2018)
Conference Proceeding
SALEH, A., ABDEL-NASSER, M., SARKER, M.M.K., SINGH, V.K., ABDULWAHAB, S., SAFFARI, N., GARCIA, M.A. and PUIG, D. 2018. Deep visual embedding for image classification. In Proceedings of 2018 international conference on Innovative trends in computer engineering (ITCE 2018), 19-21 February 2018, Aswan, Egypt. Piscataway: IEEE [online], pages 31-35. Available from: https://doi.org/10.1109/ITCE.2018.8316596

This paper proposes a new visual embedding method for image classification. It goes further in the analogy with textual data and allows us to read visual sentences in a certain order as in the case of text. The proposed method considers the spatial r... Read More about Deep visual embedding for image classification..

A novel license plate character segmentation method for different types of vehicle license plates. (2014)
Conference Proceeding
SARKER, M.M.K. and SONG, M.K. 2014. A novel license plate character segmentation method for different types of vehicle license plates. In Proceedings of 2014 International conference on Information and communication technology convergence (ICTC 2014): ICT convergence towards hyper-connected society, 22-24 October 2014, Busan, South Korea. Piscataway: IEEE [online], pages 84-88. Available from: https://doi.org/10.1109/ictc.2014.6983089

License plate character segmentation (LPCS) is a very important part of vehicle license plate recognition (LPR) system. The accuracy of LPR system widely depends on two parts; namely license plate detection (LPD) and LPCS. Different country has diffe... Read More about A novel license plate character segmentation method for different types of vehicle license plates..