Deep Convolution Neural Network sharing for the multi-label images classification

S Coulibaly, B Kamsu-Foguem, D Kamissoko… - Machine learning with …, 2022 - Elsevier
Addressing issues related to multi-label classification is relevant in many fields of
applications. In this work. We present a multi-label classification architecture based on Multi …

[HTML][HTML] A survey on Named Entity Recognition—datasets, tools, and methodologies

B Jehangir, S Radhakrishnan, R Agarwal - Natural Language Processing …, 2023 - Elsevier
Natural language processing (NLP) is crucial in the current processing of data because it
takes into account many sources, formats, and purposes of data as well as information from …

Hierarchical shared transfer learning for biomedical named entity recognition

Z Chai, H **, S Shi, S Zhan, L Zhuo, Y Yang - BMC bioinformatics, 2022 - Springer
Background Biomedical named entity recognition (BioNER) is a basic and important medical
information extraction task to extract medical entities with special meaning from medical …

Improved performance and robustness of multi-task representation learning with consistency loss between pretexts for intracranial hemorrhage identification in head …

S Kyung, K Shin, H Jeong, KD Kim, J Park, K Cho… - Medical Image …, 2022 - Elsevier
With the recent development of deep learning, the classification and segmentation tasks of
computer-aided diagnosis (CAD) using non-contrast head computed tomography (NCCT) …

[HTML][HTML] A clinical named entity recognition model using pretrained word embedding and deep neural networks

A Dash, S Darshana, DK Yadav, V Gupta - Decision Analytics Journal, 2024 - Elsevier
Abstract Clinical Named Entity Recognition (NER) within Electronic Medical Records
(EMRs) has seen substantial research attention. Since much clinical information resides in …

On the use of knowledge transfer techniques for biomedical named entity recognition

T Mehmood, I Serina, A Lavelli, L Putelli, A Gerevini - Future Internet, 2023 - mdpi.com
Biomedical named entity recognition (BioNER) is a preliminary task for many other tasks, eg,
relation extraction and semantic search. Extracting the text of interest from biomedical …

Deep learning based convolutional neural network structured new image classification approach for eye disease identification

I Topaloglu - Scientia Iranica, 2023 - scientiairanica.sharif.edu
A deep learning-based convolutional artificial neural networks structured a new image
classification method approach was implemented in the study. Sample application was …

A performance comparison of different cloud-based natural language understanding services for an Italian e-learning platform

M Zubani, L Sigalini, I Serina, L Putelli, AE Gerevini… - Future Internet, 2022 - mdpi.com
During the COVID-19 pandemic, the corporate online training sector has increased
exponentially and online course providers had to implement innovative solutions to be more …

Automated Identification and Classification of Plant Species in Heterogeneous Plant Areas Using Unmanned Aerial Vehicle-Collected RGB Images and Transfer …

G Tariku, I Ghiglieno, G Gilioli, F Gentilin, S Armiraglio… - Drones, 2023 - mdpi.com
Biodiversity regulates agroecosystem processes, ensuring stability. Preserving and restoring
biodiversity is vital for sustainable agricultural production. Species identification and …

[HTML][HTML] New unfreezing strategy of transfer learning in satellite imagery for map** the diversity of slum areas: A case study in Kenitra city—Morocco

T El Moudden, M Amnai, A Choukri, Y Fakhri… - Scientific African, 2024 - Elsevier
The purpose behind this paper research is to localize and detect, for the first time, three
types of shantytowns that can exist in both urban and rural areas in Morocco. The reason …