ProCDNet: prostate cancer detection network using quantum machine learning with enhanced addax optimization

Hybrid fusion of E-nose and computer vision using optimized deep learning and machine learning for robust plant leaf recognition

Pouya Bohlol, Mohammad Hasan Sabet Dizavandi, Syed Saeid Mohtasebi, Mahmoud Omid

Abstract The fusion multi-sensory system with optimized deep learning and machine learning algorithms appeared to synergize difficult paradigms in precision agriculture and boost recognition of various plant species. In this study, an electronic nose (E-nose) system with eight MO…Read more

Analysis and comparison of two selected machine learning algorithms for enhancing wireless sensor network protocols

Abdulla Juwaied, Lidia Jackowska-Strumillo

Optimization-enhanced machine failure classification using critical sensor features and hybrid learning models with advanced optimization techniques

Jinqin Tang, Junling Chai, Jinkun Dai, Jicheng Feng, Ruiqing Tian, Jijing Mei, et al.

BEML-sonar: a bio-inspired echolocation and machine learning-enhanced SONAR for underwater object detection and navigation

C. Kishor Kumar Reddy, Vijaya Sindhoori Kaza, P. R. Anisha, Surbhi B. Khan, Asma Alshuhail, Ahlam Almusharraf

Abstract Traditional SONAR systems are widely used for underwater object detection and navigation; however, they suffer from high energy consumption, noise interference, and signal degradation in varying aquatic conditions. Inspired by biological echolocation, we propose a novel…Read more

Weakly supervised attention-based learning supports breast cancer detection on deep ultraviolet-excitation fluorescence images

Ryuta Nakao, Tomoya Matsui, Masatoshi Abe, Mizuki Honda, Osamu Inamori, Ippei Takada, et al.

Abstract Microscopy with ultraviolet surface excitation (MUSE) enables rapid fluorescence imaging of fresh tissue surfaces without conventional sectioning, but its appearance differs from that of haematoxylin and eosin-stained slides. Pixel- or patch-level annotation for deep lea…Read more

A machine learning–based optimal charging strategy for PV-assisted electric vehicle systems incorporating second-life batteries under degradation constraints

Ahmed Ezzat, Ayman S. Abdel-Khalik, Ragi A. Hamdy, Mostafa S. Hamad

Abstract The rapid expansion of electric vehicles (EVs) and residential photovoltaic (PV) systems has created new challenges in battery charging management, particularly due to the variability of renewable energy, grid limitations, and battery aging effects. In this work, we pres…Read more