Outputs (40)

Participatory Science and Machine Learning Applied to Millions of Sources in the Hobby-Eberly Telescope Dark Energy Experiment (2024)
Journal Article
House, L. R., Gebhardt, K., Finkelstein, K., Mentuch Cooper, E., Davis, D., Farrow, D., & Schneider, D. P. (2024). Participatory Science and Machine Learning Applied to Millions of Sources in the Hobby-Eberly Telescope Dark Energy Experiment. The Astrophysical journal, 975(2), Article 172. https://doi.org/10.3847/1538-4357/ad782c

We are merging a large participatory science effort with machine learning to enhance the Hobby–Eberly Telescope Dark Energy Experiment (HETDEX). Our overall goal is to remove false positives, allowing us to use lower signal-to-noise data and sources... Read More about Participatory Science and Machine Learning Applied to Millions of Sources in the Hobby-Eberly Telescope Dark Energy Experiment.

LLM Based Cross Modality Retrieval to Improve Recommendation Performance (2024)
Presentation / Conference Contribution
Anwaar, F., Khan, A. M., & Khalid, M. (2024, August). LLM Based Cross Modality Retrieval to Improve Recommendation Performance. Presented at 2024 29th International Conference on Automation and Computing (ICAC), Sunderland, UK

The metadata of items and users play an important role in improving the decision-making process in the Recom-mender System. In recent times, web scraping-based techniques have been widely utilized to extract explicit user and item meta-data from diff... Read More about LLM Based Cross Modality Retrieval to Improve Recommendation Performance.

A Single Shot Multi-Head Gender, Age, and Landmarks Detection using Shared Convolution Features (2024)
Presentation / Conference Contribution
Khan, G., Pimbblet, K., Wertheim, K., & Ahmed, W. (2024, August). A Single Shot Multi-Head Gender, Age, and Landmarks Detection using Shared Convolution Features. Presented at 2024 29th International Conference on Automation and Computing (ICAC), Sunderland, United Kingdom

Considering the face as a vital and most informative portion of the human body, it reflects different high-level information about an individual. This high-level information includes Age, Gender, and Emotion. Facial muscles' shape and movement can be... Read More about A Single Shot Multi-Head Gender, Age, and Landmarks Detection using Shared Convolution Features.

Eco-Driving With Partial Wireless Charging Lane at Signalized Intersection: A Reinforcement Learning Approach (2024)
Journal Article
Ren, X., Lai, C. S., Guo, Z., & Taylor, G. (2024). Eco-Driving With Partial Wireless Charging Lane at Signalized Intersection: A Reinforcement Learning Approach. IEEE Transactions on Consumer Electronics, https://doi.org/10.1109/TCE.2024.3482101

Consumer electronics such as advanced GPS,vehicular sensors,inertial measurement units (IMUs),and wireless modules integrate vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) within internet of thing (IoT),enabling connected autonomous ele... Read More about Eco-Driving With Partial Wireless Charging Lane at Signalized Intersection: A Reinforcement Learning Approach.

Crafting Tomorrow's Evaluations: Assessment Design Strategies in the Era of Generative AI (2024)
Presentation / Conference Contribution
Kadel, R., Mishra, B. K., Shailendra, S., Abid, S., Rani, M., & Mahato, S. P. (2024, July). Crafting Tomorrow's Evaluations: Assessment Design Strategies in the Era of Generative AI. Presented at 2024 International Symposium on Educational Technology, ISET 2024, Macau

In recent years, no other technology has revolutionised our life as Generative Artificial Intelligence (GenAI). GenAI has gained the attention of a myriad of users in almost every profession. Its advancement has had an intense impact on education, si... Read More about Crafting Tomorrow's Evaluations: Assessment Design Strategies in the Era of Generative AI.

A Responsible AI Perspective to implementing Generative AI in Personalized Healthcare: Implications, Challenges and Future Directions (2024)
Presentation / Conference Contribution
Fagbola, T. M., Dhiman, A., Mboli, J., & Mishra, B. (2024, October). A Responsible AI Perspective to implementing Generative AI in Personalized Healthcare: Implications, Challenges and Future Directions. Paper presented at 1st International Workshop on Responsible AI (RAI) for Healthcare and Net Zero, IIT Madras, Chennai, India

Generative AI (GenAI) is transforming personalized healthcare by enabling customized treatment plans, advancing drug discovery, and offering targeted diagnostic support. While these advancements offer significant potential, they also present complex... Read More about A Responsible AI Perspective to implementing Generative AI in Personalized Healthcare: Implications, Challenges and Future Directions.

Digital Health and Indoor Air Quality: An IoT- Driven Human-Centred Visualisation Platform for Behavioural Change and Technology Acceptance (2024)
Presentation / Conference Contribution
Kureshi, R. R., Mazumdar, S., Mishra, B. K., Li, X., & Thakker, D. (2023, December). Digital Health and Indoor Air Quality: An IoT- Driven Human-Centred Visualisation Platform for Behavioural Change and Technology Acceptance. Presented at 4th International Conference on Distributed Sensing and Intelligent Systems (ICDSIS 2023), Dubai, UAE

The detrimental effects of air pollutants on human health have prompted increasing concerns regarding indoor air quality (IAQ). The emergence of digital health interventions and citizen science initiatives has provided new avenues for raising awarene... Read More about Digital Health and Indoor Air Quality: An IoT- Driven Human-Centred Visualisation Platform for Behavioural Change and Technology Acceptance.

Deep Learning-Based Colorectal Cancer Image Segmentation and Classification: A Concise Bibliometric Analysis (2024)
Presentation / Conference Contribution
Fagbola, T. M., Aderemi, E. T., & Thakur, C. S. (2024, August). Deep Learning-Based Colorectal Cancer Image Segmentation and Classification: A Concise Bibliometric Analysis. Presented at 7th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (icABCD), Mauritius

The use of Deep Learning (DL)-based methods for Colorectal Cancer (CRC) classification and segmentation has gained significant attention in recent times. This study employs a bibliometric analysis to investigate the state-of-The-art research on DL-ba... Read More about Deep Learning-Based Colorectal Cancer Image Segmentation and Classification: A Concise Bibliometric Analysis.

DeepCAI-V3: Improved Brain Tumor Classification from Noisy Brain MR Images using Convolutional Autoencoder and Inception-V3 Architecture (2024)
Presentation / Conference Contribution
Babaferi, E. V., Fagbola, T. M., & Thakur, C. S. (2024, August). DeepCAI-V3: Improved Brain Tumor Classification from Noisy Brain MR Images using Convolutional Autoencoder and Inception-V3 Architecture. Presented at 7th International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems, Mauritius

Brain tumors are abnormal cell growths within the brain tissues, necessitating their early detection towards effective treatment. To achieve this, high-quality brain images via medical imaging techniques, such as Magnetic Resonance Imaging (MRI), are... Read More about DeepCAI-V3: Improved Brain Tumor Classification from Noisy Brain MR Images using Convolutional Autoencoder and Inception-V3 Architecture.

Ensemble Supervised Learning-based Approaches for Mobile Network Coverage and Quality Predictions in a University Setting (2024)
Presentation / Conference Contribution
Okiemute Osiezagha, M., Kumar Mishra, B., & Fagbola, T. M. (2024, August). Ensemble Supervised Learning-based Approaches for Mobile Network Coverage and Quality Predictions in a University Setting. Paper presented at International Conference on Intelligent Systems with Applications in Communications, Computing and IoT (ICISCCI-2K24), Vardhaman College of Engineering, Hyderabad, India

This research explores the application of predictive analytics through Machine Learning (ML) algorithms to enhance Mobile Network Key Performance Indicators (KPIs), specifically focusing on Reference Signal Received Power (RSRP) as coverage and Refer... Read More about Ensemble Supervised Learning-based Approaches for Mobile Network Coverage and Quality Predictions in a University Setting.