Zobrazeno 1 - 10
of 8 799
pro vyhledávání: '"Sheeba, A."'
While deep learning has significantly advanced automatic plant disease detection through image-based classification, improving model explainability remains crucial for reliable disease detection. In this study, we apply the Automated Concept-based Ex
Externí odkaz:
http://arxiv.org/abs/2412.07408
Deep Learning (DL) techniques are increasingly applied in scientific studies across various domains to address complex research questions. However, the methodological details of these DL models are often hidden in the unstructured text. As a result,
Externí odkaz:
http://arxiv.org/abs/2411.09269
Autor:
Sharma, Anantha, John, Sheeba Elizabeth, Nikroo, Fatemeh Rezapoor, Bhatt, Krupali, Zambre, Mrunal, Wikhe, Aditi
The growth of digital documents presents significant challenges in efficient management and knowledge extraction. Traditional methods often struggle with complex documents, leading to issues such as hallucinations and high latency in responses from L
Externí odkaz:
http://arxiv.org/abs/2411.05936
Recently, there has been a growing interest in Multimodal Large Language Models (MLLMs) due to their remarkable potential in various tasks integrating different modalities, such as image and text, as well as applications such as image captioning and
Externí odkaz:
http://arxiv.org/abs/2409.18753
Autor:
Ahmed, Waqas, Kommineni, Vamsi Krishna, König-Ries, Birgitta, Gaikwad, Jitendra, Gadelha, Luiz, Samuel, Sheeba
Artificial Intelligence (AI) is revolutionizing biodiversity research by enabling advanced data analysis, species identification, and habitats monitoring, thereby enhancing conservation efforts. Ensuring reproducibility in AI-driven biodiversity rese
Externí odkaz:
http://arxiv.org/abs/2407.07550
Autor:
Samuel, Sheeba, Mietchen, Daniel
The way in which data are shared can affect their utility and reusability. Here, we demonstrate how data that we had previously shared in bulk can be mobilized further through a knowledge graph that allows for much more granular exploration and inter
Externí odkaz:
http://arxiv.org/abs/2404.12935
The conventional process of building Ontologies and Knowledge Graphs (KGs) heavily relies on human domain experts to define entities and relationship types, establish hierarchies, maintain relevance to the domain, fill the ABox (or populate with inst
Externí odkaz:
http://arxiv.org/abs/2403.08345
Autor:
Perveen, Shahida, Qurat-ul-Ain, Iqbal, Sarosh, Wajid, Sheeba, khan, Khalid Muhammad, Choudhary, Muhammad Iqbal
To investigate1,1-Diphenyl-2-picrylhydrazyl (DPPH) and superoxide radical (SOR) 17 scavenging activities of 2-oxo-1,2,3,4-tetrahydropyrimidines derivatives. Free radicals are 18 highly unstable and reactive molecules/atoms. In the body, free radicals
Externí odkaz:
http://arxiv.org/abs/2310.10063
Autor:
Sheeba Armoogum, Kezhilen Motean, Deshinta Arrova Dewi, Tri Basuki Kurniawan, Jureerat Kijsomporn
Publikováno v:
Emerging Science Journal, Vol 8, Iss 6, Pp 2373-2384 (2024)
Breast cancer is currently the most prevalent type of cancer in women, with a growing number of fatalities worldwide. Different imaging methods like mammography, computed tomography, Magnetic Resonance Imaging, ultrasound, and biopsies assist in dete
Externí odkaz:
https://doaj.org/article/0f8e09b3925c4ccf98240242976711e6
Autor:
Sheeba Ravi, Kannan Krishnamoorthy, Rajini Senthil, Premnath Dhasaram, Monisha Venkatesan, R Iswarya, T. Manjubairavi
Publikováno v:
CHRISMED Journal of Health and Research, Vol 11, Iss 2, Pp 80-84 (2024)
Context: Smartphones have revolutionized, and become an integral part of a child’s life. The child’s interaction with these modern devices needs to be assessed because it could have an enormous effect on their behavior, sleep habits, and psycholo
Externí odkaz:
https://doaj.org/article/767cca1782c0412d8657e45da1a95d55