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Machine learning

FedNolowe: A normalized loss-based weighted aggregation strategy for robust federated learning in heterogeneous environments

Duy-Dong Le, Tuong-Nguyen Huynh, [ ... ], Pham The Bao

Simple modification of the upper confidence bound algorithm by generalized weighted averages

Nobuhito Manome, Shuji Shinohara, Ung-il Chung

Nuclei segmentation and classification from histopathology images using federated learning for end-edge platform

Anjir Ahmed Chowdhury, S M Hasan Mahmud, [ ... ], Yunyoung Nam

Segmentation-based lightweight multi-class classification model for crop disease detection, classification, and severity assessment using DCNN

Chatla Subbarayudu, Mohan Kubendiran

Machine learning driven biomarker selection for medical diagnosis

Divyagna Bavikadi, Ayushi Agarwal, [ ... ], Paulo Shakarian

Odor classification: Exploring feature performance and imbalanced data learning techniques

Durgesh Ameta, Surendra Kumar, [ ... ], Tushar Sandhan

From blender to farm: Transforming controlled environment agriculture with synthetic data and SwinUNet for precision crop monitoring

Kimia Aghamohammadesmaeilketabforoosh, Joshua Parfitt, Soodeh Nikan, Joshua M. Pearce

TransembleNet: Enhancing vector mosquito species classification through transfer learning-based ensemble model

Abdullah Al Maruf, Md. Mahmudul Haque, [ ... ], Zeyar Aung

AI-delirium guard: Predictive modeling of postoperative delirium in elderly surgical patients

Sri Harsha Boppana, Divyansh Tyagi, [ ... ], C. David Mintz

Self-supervised learning framework for efficient classification of endoscopic images using pretext tasks

Shima Ayyoubi Nezhad, Golnaz Tajeddin, Toktam Khatibi, Masoudreza Sohrabi

Chi² weighted ensemble: A multi-layer ensemble approach for skin lesion classification using a novel framework - optimized RegNet synergy with Attention-Triplet

Anwar Hossain Efat

Intelligent recognition of human activities using deep learning techniques

Shazab Bashir, Arfan Jaffar, [ ... ], Sohail Masood Bhatti

Automatic time in bed detection from hip-worn accelerometers for large epidemiological studies: The Tromsø Study

Marc Weitz, Shaheen Syed, [ ... ], Alexander Horsch

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