Md. Adnan Arefeen

Orcid: 0000-0001-6486-8181

According to our database1, Md. Adnan Arefeen authored at least 12 papers between 2019 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2023
LeanContext: Cost-Efficient Domain-Specific Question Answering Using LLMs.
CoRR, 2023

FactionFormer: Context-Driven Collaborative Vision Transformer Models for Edge Intelligence.
Proceedings of the 2023 IEEE International Conference on Smart Computing, 2023

MetaMorphosis: Task-oriented Privacy Cognizant Feature Generation for Multi-task Learning.
Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation, 2023

2022
Neural Network-Based Undersampling Techniques.
IEEE Trans. Syst. Man Cybern. Syst., 2022

Chimera: Context-Aware Splittable Deep Multitasking Models for Edge Intelligence.
Proceedings of the 2022 IEEE International Conference on Smart Computing, 2022

FrameHopper: Selective Processing of Video Frames in Detection-driven Real-Time Video Analytics.
Proceedings of the 18th International Conference on Distributed Computing in Sensor Systems, 2022

2021
EARLIN: Early Out-of-Distribution Detection for Resource-Efficient Collaborative Inference.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Towards resource-efficient detection-driven processing of multi-stream videos.
Proceedings of the ACM MobiCom '21: The 27th Annual International Conference on Mobile Computing and Networking, 2021

Cost effective processing of detection-driven video analytics at the edge.
Proceedings of the HotEdgeVideo@MobiCom 2021: Proceedings of the 3rd ACM Workshop on Hot Topics in Video Analytics and Intelligent Edges, 2021

A Lightweight Relu-Based Feature Fusion For Aerial Scene Classification.
Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

TransJury: Towards Explainable Transfer Learning through Selection of Layers from Deep Neural Networks.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2019
CerebLearn: Biologically Motivated Learning Rule for Artificial Feedforward Neural Networks.
Proceedings of International Joint Conference on Computational Intelligence, 2019


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