10 citations · 13 across the 5 of their papers we have counts for
5 papers
iRAG: Advancing RAG for Videos with an Incremental Approach
Md Adnan Arefeen, Biplob Debnath, Md Yusuf Sarwar Uddin +1
Retrieval-augmented generation (RAG) systems combine the strengths of language generation and information retrieval to power many real-world applications like chatbots. Use of RAG…
MetaMorphosis: Task-oriented Privacy Cognizant Feature Generation for Multi-task Learning
Md Adnan Arefeen, Zhouyu Li, Md Yusuf Sarwar Uddin +1
With the growth of computer vision applications, deep learning, and edge computing contribute to ensuring practical collaborative intelligence (CI) by distributing the workload amo…
FrameHopper: Selective Processing of Video Frames in Detection-driven Real-Time Video Analytics
Md Adnan Arefeen, Sumaiya Tabassum Nimi, Md Yusuf Sarwar Uddin
Detection-driven real-time video analytics require continuous detection of objects contained in the video frames using deep learning models like YOLOV3, EfficientDet. However, runn…
EARLIN: Early Out-of-Distribution Detection for Resource-efficient Collaborative Inference
Sumaiya Tabassum Nimi, Md Adnan Arefeen, Md Yusuf Sarwar Uddin +1
Collaborative inference enables resource-constrained edge devices to make inferences by uploading inputs (e.g., images) to a server (i.e., cloud) where the heavy deep learning mode…
A Lightweight ReLU-Based Feature Fusion for Aerial Scene Classification
Md Adnan Arefeen, Sumaiya Tabassum Nimi, Md Yusuf Sarwar Uddin +1
In this paper, we propose a transfer-learning based model construction technique for the aerial scene classification problem. The core of our technique is a layer selection strateg…