Zobrazeno 1 - 10
of 11 159
pro vyhledávání: '"Talukder A"'
Publikováno v:
Journal of Multidisciplinary Healthcare, Vol Volume 15, Pp 1101-1110 (2022)
Ashis Talukder,1 Shaharior Rahman Razu,2 Sheikh Mohammad Alif,3 Muhammad Aziz Rahman,4,5 Sheikh Mohammed Shariful Islam6 1Statistics Discipline, Khulna University, Khulna, 9208, Bangladesh; 2Sociology Discipline, Khulna University, Khulna, 9208, Bang
Externí odkaz:
https://doaj.org/article/e3c599081ddc4dd281bb1eab3e329d7f
Autor:
Powadi, Anirudha, Jubery, Talukder Zaki, Tross, Michael C., Schnable, James C., Ganapathysubramanian, Baskar
This study introduces a compositional autoencoder (CAE) framework designed to disentangle the complex interplay between genotypic and environmental factors in high-dimensional phenotype data to improve trait prediction in plant breeding and genetics
Externí odkaz:
http://arxiv.org/abs/2410.19922
Skin cancer is a serious and potentially fatal disease caused by DNA damage. Early detection significantly increases survival rates, making accurate diagnosis crucial. In this groundbreaking study, we present a hybrid framework based on Deep Learning
Externí odkaz:
http://arxiv.org/abs/2410.14489
Autor:
Puppala, Sai, Hossain, Ismail, Alam, Md Jahangir, Talukder, Sajedul, Talukder, Zahidur, Bahauddin, Syed
Federated Learning (FL) has emerged as a transformative approach for enabling distributed machine learning while preserving user privacy, yet it faces challenges like communication inefficiencies and reliance on centralized infrastructures, leading t
Externí odkaz:
http://arxiv.org/abs/2407.18387
Our study presents a multifaceted approach to enhancing user interaction and content relevance in social media platforms through a federated learning framework. We introduce personalized GPT and Context-based Social Media LLM models, utilizing federa
Externí odkaz:
http://arxiv.org/abs/2408.05243
Our paper introduces a novel approach to social network information retrieval and user engagement through a personalized chatbot system empowered by Federated Learning GPT. The system is designed to seamlessly aggregate and curate diverse social medi
Externí odkaz:
http://arxiv.org/abs/2408.05242
Autor:
Arshad, Muhammad Arbab, Jubery, Talukder Zaki, Roy, Tirtho, Nassiri, Rim, Singh, Asheesh K., Singh, Arti, Hegde, Chinmay, Ganapathysubramanian, Baskar, Balu, Aditya, Krishnamurthy, Adarsh, Sarkar, Soumik
Plant stress phenotyping traditionally relies on expert assessments and specialized models, limiting scalability in agriculture. Recent advances in multimodal large language models (LLMs) offer potential solutions to this challenge. We present AgEval
Externí odkaz:
http://arxiv.org/abs/2407.19617
Autor:
Puppala, Sai, Hossain, Ismail, Alam, Md Jahangir, Talukder, Sajedul, Ferdaus, Jannatul, Hasan, Mahedi, Pisupati, Sameera, Mathukumilli, Shanmukh
Federated learning has become a significant approach for training machine learning models using decentralized data without necessitating the sharing of this data. Recently, the incorporation of generative artificial intelligence (AI) methods has prov
Externí odkaz:
http://arxiv.org/abs/2407.18358
User activities can influence their subsequent interactions with a post, generating interest in the user. Typically, users interact with posts from friends by commenting and using reaction emojis, reflecting their level of interest on social media su
Externí odkaz:
http://arxiv.org/abs/2407.09747
Social media platforms are extensively used for sharing personal emotions, daily activities, and various life events, keeping people updated with the latest happenings. From the moment a user creates an account, they continually expand their network
Externí odkaz:
http://arxiv.org/abs/2407.09691