Energy-efficient wireless sensor network for urban groundwater level monitoring using machine learning and sink mobility. [PDF]
Manchanda R +8 more
europepmc +1 more source
A Hybrid Transfer Learning Framework for Brain Tumor Diagnosis
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 +11 more
wiley +1 more source
Building the connectome of a small brain with a simple stochastic developmental generative model. [PDF]
Richter O, Schneidman E.
europepmc +1 more source
We present a novel AI‐integrated implantation‐on‐chip platform that enables mimicking and monitoring the maternal–fetal interactions at the early phases of human embryo implantation with high spatiotemporal resolution. The complexity of the trophoblast invasion process was addressed by conducting the analysis at global (rate of invasion) and local ...
Joanna Filippi +12 more
wiley +1 more source
What does it take to learn the rules of RNA base pairing? A lot less than you may think. [PDF]
Pratap JS, Krueger RK, Rivas E.
europepmc +1 more source
Scene‐Customized Learning for Multi‐Depth 3D Phase‐Only Hologram Generation
Scene‐customized geometric modeling constructs GM‐4K, a controllable 4K RGB‐D dataset for learning‐based multi‐depth hologram generation. By tuning intensity spectra and depth‐region sampling, the dataset reveals how training‐data statistics affect phase‐only hologram encoding and supports a spectral test framework for evaluating model generalization ...
Yanan Zhang +5 more
wiley +1 more source
MicroRNA target gene prediction model based on input-feature dependency and sample data expansion technique. [PDF]
Shao Y, Li Y, Zhai H, Dong S.
europepmc +1 more source
The phase discontinuity problem—where the cyclic nature of phase angles causes catastrophic errors near the ±π boundary—is a fundamental obstacle in learning‐based reconfigurable intelligent surface (RIS) optimization. A phase‐aware hybrid CNN–LSTM framework resolves this by decomposing phase predictions into sine–cosine components, mapping circular ...
Seda Savaşçı Şen +3 more
wiley +1 more source
Energy‐Aware Perturbation Optimization for Memristor‐Array Convolutional Neural Networks
Memristor‐array inference becomes more energy efficient when layer inputs are reshaped before computation. Sinusoidal perturbation encoding with dual‐threshold screening reduces active voltage pulses and contracts ADC input‐current ranges, jointly lowering crossbar and peripheral energy while preserving accuracy across hardware MNIST validation, deep ...
Ao Xu +6 more
wiley +1 more source
A method for multi-criteria decision making with probabilistic linguistic term based on cloud TOPSIS. [PDF]
Almandeel A, Rao C, Zhang X, Qi H.
europepmc +1 more source

