Results 201 to 210 of about 20,562 (267)

Interpretable CRAM‑Enhanced Lightweight Dual‑Branch CNN for Real‑Time Breast Cancer Histopathology in Internet‑of‑Medical‑Things Environments

Small, Volume 22, Issue 26, 8 May 2026.
This study presents an interpretable, lightweight hybrid deep learning model for real‐time analysis of breast cancer histopathology in IoMT‐enabled diagnostic systems. By integrating MobileNetV2 and EfficientNet‐B0 with a novel contextual recurrent attention module (CRAM), the framework achieves near‐perfect accuracy while providing transparent Grad ...
Roseline Oluwaseun Ogundokun, Rotimi‐Williams Bello, Pius Adewale Owolawi, Rytis Maskeliūnas, Abdulsatar Abduljabbar Sultan   +4 more
wiley   +1 more source

Deep Learning-Driven Automatic Segmentation of Weeds and Crops in UAV Imagery. [PDF]

Sensors (Basel)
Tao J, Qiao Q, Song J, Sun S, Chen Y, Wu Q, Liu Y, Xue F, Wu H, Zhao F.   +9 more
europepmc   +1 more source

Unpacking Climate Literacy in Science Education: What Explains Students' Willingness to Engage in Climate Action?

Journal of Research in Science Teaching, Volume 63, Issue 4-5, Page 393-411, May 2026.
ABSTRACT Due to the far‐reaching and life‐threatening consequences of climate change, science education is becoming increasingly important for preparing students to become climate literate citizens. Climate literacy, which encompasses knowledge, skills, and attitudes related to climate change, can provide a strong foundation for informed climate action.
Carola Garrecht, Nina Christenson, Niklas Gericke, Jesper Haglund, Jari Appelgren, Ute Harms   +5 more
wiley   +1 more source

An Improved Robust ESKF Fusion Positioning Method with a Novel UWB-VIO Initialization. [PDF]

Sensors (Basel)
Wang C, Li B, Duan Y, Sui X, Shi Z, Gao S, Zhang Z, Chen J.   +7 more
europepmc   +1 more source

PlumeDEBuG: Data‐Informed Modeling for Synthetic Bubble Plume Image Generation

Water Resources Research, Volume 62, Issue 5, May 2026.
Abstract Bubble plumes play an important role in both natural and engineered aquatic systems. Optical imaging has been widely used to study bubble size distributions, meandering, and plume growth. Machine learning (ML) offers new opportunities in analyzing optical images of bubble plumes.
Xuchen Ying, Binbin Wang
wiley   +1 more source

Advanced stacked modeling techniques for material porosity estimation via high-resolution computed tomography imaging. [PDF]

Sci Rep
Kim B, K R SP, Natarajan Y, Danushkumar, Park S, Pyo S.   +5 more
europepmc   +1 more source

Criteria for selecting the Paganin‐filter reconstruction parameter in X‐ray phase‐contrast tomography

Journal of Synchrotron Radiation, Volume 33, Issue 3, Page 746-758, May 2026.
The development of a criterion for near‐optimal selection of the Paganin‐filter parameter based on noise power analysis measured via an image's noise power spectrum is described.The Paganin filter, widely employed in propagation‐based phase‐contrast X‐ray computed tomography with synchrotron light, attenuates phase effects and suppresses high‐frequency
Eduardo X. Miqueles, Everton L. de Oliveira, Murilo Carvalho, David M. Paganin   +3 more
wiley   +1 more source

Dioptric blur is not fully reflected by VEP-based visual acuity estimates. [PDF]

Doc Ophthalmol
Amega DAD, Haldina J, Toews I, Philippin H, Hoffmann MB, Morny EKA, Heinrich SP.   +6 more
europepmc   +1 more source

Unveiling the factors of aesthetic preferences with explainable AI

British Journal of Psychology, Volume 117, Issue 2, Page 444-478, May 2026.
Abstract The allure of aesthetic appeal in images captivates our senses, yet the underlying intricacies of aesthetic preferences remain elusive. In this study, we pioneer a novel perspective by utilizing several different machine learning (ML) models that focus on aesthetic attributes known to influence preferences.
Derya Soydaner, Johan Wagemans
wiley   +1 more source

Deep-blur: Blind identification and deblurring with convolutional neural networks. [PDF]

Biol Imaging
Debarnot V, Weiss P.
europepmc   +1 more source