Výsledky vyhledávání - "Khan, Faisal A. A."

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BanLemma: A Word Formation Dependent Rule and Dictionary Based Bangla Lemmatizer

Autor: Afrin, Sadia, Chowdhury, Md. Shahad Mahmud, Islam, Md. Ekramul, Khan, Faisal Ahamed, Chowdhury, Labib Imam, Mahtab, MD. Motahar, Chowdhury, Nazifa Nuha, Forkan, Massud, Kundu, Neelima, Arif, Hakim, Rashid, Mohammad Mamun Or, Amin, Mohammad Ruhul, Mohammed, Nabeel

Lemmatization holds significance in both natural language processing (NLP) and linguistics, as it effectively decreases data density and aids in comprehending contextual meaning. However, due to the highly inflected nature and morphological richness,

Externí odkaz: http://arxiv.org/abs/2311.03078

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SentiGOLD: A Large Bangla Gold Standard Multi-Domain Sentiment Analysis Dataset and its Evaluation

Autor: Islam, Md. Ekramul, Chowdhury, Labib, Khan, Faisal Ahamed, Hossain, Shazzad, Hossain, Sourave, Rashid, Mohammad Mamun Or, Mohammed, Nabeel, Amin, Mohammad Ruhul

This study introduces SentiGOLD, a Bangla multi-domain sentiment analysis dataset. Comprising 70,000 samples, it was created from diverse sources and annotated by a gender-balanced team of linguists. SentiGOLD adheres to established linguistic conven

Externí odkaz: http://arxiv.org/abs/2306.06147

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Development, Optimization, and Deployment of Thermal Forward Vision Systems for Advance Vehicular Applications on Edge Devices

Autor: Farooq, Muhammad Ali, Shariff, Waseem, Khan, Faisal, Corcoran, Peter

In this research work, we have proposed a thermal tiny-YOLO multi-class object detection (TTYMOD) system as a smart forward sensing system that should remain effective in all weather and harsh environmental conditions using an end-to-end YOLO deep le

Externí odkaz: http://arxiv.org/abs/2301.07613

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LMFLOSS: A Hybrid Loss For Imbalanced Medical Image Classification

Autor: Sadi, Abu Adnan, Chowdhury, Labib, Jahan, Nusrat, Rafi, Mohammad Newaz Sharif, Chowdhury, Radeya, Khan, Faisal Ahamed, Mohammed, Nabeel

With advances in digital technology, the classification of medical images has become a crucial step for image-based clinical decision support systems. Automatic medical image classification represents a pivotal domain where the use of AI holds the po

Externí odkaz: http://arxiv.org/abs/2212.12741

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