10 citations · 19 across the 12 of their papers we have counts for
7 papers · 1 filter
ChitraMiti: Benchmarking Visual Grounding and Modality Reliance in Bengali Geometric Reasoning
Khan Raiyan Ibne Reza, Sanjana Aktar Maria, Sumaiya Tabassum Nimi +1
Evaluation of vision-language models (VLMs) for multimodal mathematical reasoning remains limited for low-resource languages and for geometry problems that require reading a diagra…
Open-SAT: LLM-Guided Query Embedding Refinement for Open-Vocabulary Object Retrieval in Satellite Imagery
Md Adnan Arefeen, Biplob Debnath, Ravi K. Rajendran +2
In satellite applications, user queries often take the form of open-ended natural language, extending beyond a fixed set of predefined categories. This open-vocabulary nature poses…
TrafficLens: Multi-Camera Traffic Video Analysis Using LLMs
Md Adnan Arefeen, Biplob Debnath, Srimat Chakradhar
Traffic cameras are essential in urban areas, playing a crucial role in intelligent transportation systems. Multiple cameras at intersections enhance law enforcement capabilities,…
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…