Results 151 to 160 of about 390,241 (222)

Active Whisker‐Inspired Food Material Surface Property Measurement Using Deep‐Learned Mechanosensor

Advanced Intelligent Systems, EarlyView.
Herein, a new application is proposed for an active whisker sensor that mimics the movement of rat whiskers. The whiskers, which are deformed by contact with an object, provide information about surface properties. It is shown that active whisker sensors can be useful in the food industry, and data identification is performed using deep learning ...
Jieun Park, Minho Kim, Jinhyung Park, Myungrae Hong, Sunghoon Im, Damin Choi, Eunyoung Kim, Dohyeon Gong, Seokhaeng Huh, Seung‐Un Jo, ChangHwan Kim, Je‐Sung Koh, Seungyong Han, Daeshik Kang   +13 more
wiley   +1 more source

Convolutional neural network using magnetic resonance brain imaging to predict outcome from tuberculosis meningitis. [PDF]

PLoS One
Dong THK, Canas LS, Donovan J, Beasley D, Thuong-Thuong NT, Phu NH, Ha NT, Ourselin S, Razavi R, Thwaites GE, Modat M.   +10 more
europepmc   +1 more source

Clinically Informed Intelligent Classification of Ovarian Cancer Cells by Label‐Free Holographic Imaging Flow Cytometry

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Quantitative phase maps of single cells recorded in flow cytometry modality feed a hierarchical architecture of machine learning models for the label‐free identification of subtypes of ovarian cancer. The employment of a priori clinical information improves the classification performance, thus emulating the clinical application of liquid biopsy during ...
Daniele Pirone, Beatrice Cavina, Daniele Gaetano Sirico, Martina Mugnano, Vittorio Bianco, Lisa Miccio, Anna Myriam Perrone, Anna Maria Porcelli, Giuseppe Gasparre, Ivana Kurelac, Pasquale Memmolo, Pietro Ferraro   +11 more
wiley   +1 more source

Underwater Target Recognition Method Based on Singular Spectrum Analysis and Channel Attention Convolutional Neural Network. [PDF]

Sensors (Basel)
Ji F, Lu S, Ni J, Li Z, Feng W.
europepmc   +1 more source

A Review on Recent Trends of Bioinspired Soft Robotics: Actuators, Control Methods, Materials Selection, Sensors, Challenges, and Future Prospects

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This article reviews the current state of bioinspired soft robotics. The article discusses soft actuators, soft sensors, materials selection, and control methods used in bioinspired soft robotics. It also highlights the challenges and future prospects of this field.
Abhirup Sarker, Tamzid Ul Islam, Md. Robiul Islam   +2 more
wiley   +1 more source

Computer-aided cholelithiasis diagnosis using explainable convolutional neural network. [PDF]

Sci Rep
Kumar D, Mehta MA, Kotecha K, Kulkarni A.   +3 more
europepmc   +1 more source

Advancements in Machine Learning for Microrobotics in Biomedicine

Advanced Intelligent Systems, EarlyView.
Microrobotics is an innovative technology with great potential for noninvasive medical interventions. However, controlling and imaging microrobots pose significant challenges in complex environments and in living organisms. This review explores how machine learning algorithms can address these issues, offering solutions for adaptive motion control and ...
Amar Salehi, Soleiman Hosseinpour, Nasrollah Tabatabaei, Mahmoud Soltani Firouz, Niloufar Zadebana, Richard Nauber, Mariana Medina‐Sánchez   +6 more
wiley   +1 more source

Machine Learning‐Based Wind Classification by Wing Deformation in Biomimetic Flapping Robots: Biomimetic Flexible Structures Improve Wind Sensing

Advanced Intelligent Systems, EarlyView.
Strain gauges are attached to biomimetic flapping wings to investigate how wing strain sensors detect wind directions. A convolutional neural network model for wind direction classification is developed through experiments. The results reveal that wind classification is possible with strain data of only 0.2 flapping cycles, and the use of biomimetic ...
Kenta Kubota, Hiroto Tanaka
wiley   +1 more source

A Hybrid Transfer Learning Framework for Brain Tumor Diagnosis

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
A novel hybrid transfer learning approach for brain tumor classification achieves 99.47% accuracy using magnetic resonance imaging (MRI) images. By combining image preprocessing, ensemble deep learning, and explainable artificial intelligence (XAI) techniques like gradient‐weighted class activation mapping and SHapley Additive exPlanations (SHAP), the ...
Sadia Islam Tonni, Md. Alif Sheakh, Mst. Sazia Tahosin, Md. Zahid Hasan, Taslima Ferdaus Shuva, Touhid Bhuiyan, Muhammad Ali Abdullah Almoyad, Nabil Anan Orka, Md. Tanvir Rahman, Risala Tasin Khan, M. Shamim Kaiser, Mohammad Ali Moni   +11 more
wiley   +1 more source