Zobrazeno 1 - 10
of 233
pro vyhledávání: '"P., Shafin"'
Video Highlight Detection and Moment Retrieval (HD/MR) are essential in video analysis. Recent joint prediction transformer models often overlook their cross-task dynamics and video-text alignment and refinement. Moreover, most models typically use l
Externí odkaz:
http://arxiv.org/abs/2412.01558
Test-time adaptation (TTA) of 3D point clouds is crucial for mitigating discrepancies between training and testing samples in real-world scenarios, particularly when handling corrupted point clouds. LiDAR data, for instance, can be affected by sensor
Externí odkaz:
http://arxiv.org/abs/2411.14495
Autor:
Samin, Md. Nazmus Sadat, Ahad, Jawad Ibn, Medha, Tanjila Ahmed, Rahman, Fuad, Amin, Mohammad Ruhul, Mohammed, Nabeel, Rahman, Shafin
This study focuses on recognizing Bangladeshi dialects and converting diverse Bengali accents into standardized formal Bengali speech. Dialects, often referred to as regional languages, are distinctive variations of a language spoken in a particular
Externí odkaz:
http://arxiv.org/abs/2411.10879
Autor:
Ahad, Jawad Ibn, Sultan, Rafeed Mohammad, Kaikobad, Abraham, Rahman, Fuad, Amin, Mohammad Ruhul, Mohammed, Nabeel, Rahman, Shafin
This study investigates the automation of meta-analysis in scientific documents using large language models (LLMs). Meta-analysis is a robust statistical method that synthesizes the findings of multiple studies support articles to provide a comprehen
Externí odkaz:
http://arxiv.org/abs/2411.10878
As quantum computing advances, traditional cryptographic security measures, including token obfuscation, are increasingly vulnerable to quantum attacks. This paper introduces a quantum-enhanced approach to token obfuscation leveraging quantum superpo
Externí odkaz:
http://arxiv.org/abs/2411.01252
This paper presents a hybrid quantum-classical machine learning model for classification tasks, integrating a 4-qubit quantum circuit with a classical neural network. The quantum circuit is designed to encode the features of the Iris dataset using an
Externí odkaz:
http://arxiv.org/abs/2410.16344
Autor:
Ahmadi, Sahar, Cheraghian, Ali, Saberi, Morteza, Abir, Md. Towsif, Dastmalchi, Hamidreza, Hussain, Farookh, Rahman, Shafin
Recent advances in deep learning for processing point clouds hold increased interest in Few-Shot Class Incremental Learning (FSCIL) for 3D computer vision. This paper introduces a new method to tackle the Few-Shot Continual Incremental Learning (FSCI
Externí odkaz:
http://arxiv.org/abs/2410.09237
Autor:
Biswas, Amrijit, Hossain, Md. Ismail, Elahi, M M Lutfe, Cheraghian, Ali, Rahman, Fuad, Mohammed, Nabeel, Rahman, Shafin
A point cloud is a crucial geometric data structure utilized in numerous applications. The adoption of deep neural networks referred to as Point Cloud Neural Networks (PC- NNs), for processing 3D point clouds, has significantly advanced fields that r
Externí odkaz:
http://arxiv.org/abs/2408.14601
Autor:
Kabir, Muhammad Rafsan, Sultan, Rafeed Mohammad, Asif, Ihsanul Haque, Ahad, Jawad Ibn, Rahman, Fuad, Amin, Mohammad Ruhul, Mohammed, Nabeel, Rahman, Shafin
Aligning large language models (LLMs) with a human reasoning approach ensures that LLMs produce morally correct and human-like decisions. Ethical concerns are raised because current models are prone to generating false positives and providing malicio
Externí odkaz:
http://arxiv.org/abs/2408.11879
Lung diseases remain a critical global health concern, and it's crucial to have accurate and quick ways to diagnose them. This work focuses on classifying different lung diseases into five groups: viral pneumonia, bacterial pneumonia, COVID, tubercul
Externí odkaz:
http://arxiv.org/abs/2404.11428