Outputs (6)

Multi-level Dual-attention Based CNN for Macular Optical Coherence Tomography Classification (2019)
Journal Article
Mandal, B. (2019). Multi-level Dual-attention Based CNN for Macular Optical Coherence Tomography Classification. IEEE Signal Processing Letters, 1793-1797. https://doi.org/10.1109/LSP.2019.2949388

In this letter, we propose a multi-level dual-attention model to classify two common macular diseases, age-related macular degeneration (AMD) and diabetic macular edema (DME) from normal macular eye conditions using optical coherence tomography (OCT)... Read More about Multi-level Dual-attention Based CNN for Macular Optical Coherence Tomography Classification.

Towards Automatic Screening of Typical and Atypical Behaviors in Children With Autism (2019)
Presentation / Conference
Cook, A., Mandal, B., Berry, D., & Johnson, M. (2019, October). Towards Automatic Screening of Typical and Atypical Behaviors in Children With Autism. Paper presented at 2019 IEEE International Conference on Data Science and Advanced Analytics (DSAA), Washington, DC, USA

Autism spectrum disorders (ASD) impact the cognitive, social, communicative and behavioral abilities of an individual. The development of new clinical decision support systems is of importance in reducing the delay between presentation of symptoms an... Read More about Towards Automatic Screening of Typical and Atypical Behaviors in Children With Autism.

Improved Lifelog Ego-centric Video Summarization Using Ensemble of Deep Learned Object Features (2019)
Presentation / Conference
Mandal, B., & Mainwaring, P. (2019, September). Improved Lifelog Ego-centric Video Summarization Using Ensemble of Deep Learned Object Features. Presented at 30th British Machine Vision Conference, Cardiff

The ImageCLEF 2017 lifelog summarization challenge [10, 12] was established to develop a benchmark for summarizing egocentric lifelogging videos based on our daily activities, such as ‘commute to work’ or ‘cooking at home’. In this paper, we propose... Read More about Improved Lifelog Ego-centric Video Summarization Using Ensemble of Deep Learned Object Features.

Enhanced Deep Video Summarization Network (2019)
Presentation / Conference
Gonuguntla, N., Mandal, B., & Puhan, N. (2019, September). Enhanced Deep Video Summarization Network. Paper presented at 30th British Machine Vision Conference, Cardiff

Video summarization is understanding video which aims to get an abstract view of the original video sequence by the concatenation of keyframes representing the highlights of the video. In this work, we propose an enhanced deep summarization network (... Read More about Enhanced Deep Video Summarization Network.

Cross-spectral Periocular Recognition: a Survey (2019)
Conference Proceeding
Behera, S., Mandal, B., & Puhan, N. (2019). Cross-spectral Periocular Recognition: a Survey. In Emerging Research in Electronics, Computer Science and Technology (731–741). https://doi.org/10.1007/978-981-13-5802-9_64

Among many biometrics such as face, iris, fingerprint and others, periocular region has the advantages over other biometrics because it is non-intrusive and serves as a balance between iris or eye region (very stringent, small area) and the whole fac... Read More about Cross-spectral Periocular Recognition: a Survey.

Deep Convolutional Generative Adversarial Network-Based Food Recognition Using Partially Labeled Data (2019)
Journal Article
Mandal, B., Puhan, N. B., & Verma, A. (2019). Deep Convolutional Generative Adversarial Network-Based Food Recognition Using Partially Labeled Data. IEEE Sensors Letters, 3(2), Article ARTN 7000104. https://doi.org/10.1109/LSENS.2018.2886427

Traditional machine learning algorithms using hand-crafted feature extraction techniques (such as local binary pattern) have limited accuracy because of high variation in images of the same class (or intraclass variation) for food recognition tasks.... Read More about Deep Convolutional Generative Adversarial Network-Based Food Recognition Using Partially Labeled Data.