FlowRoI: fast optical-flow-based Roi extraction for high-throughput immune cell image compression. [PDF]
Xu X +7 more
europepmc +1 more source
PrOMet: Accurate and Robust Metal‐Binding Site and Type Prediction
PrOMet is a two‐stage deep learning framework for jointly predicting metal‐binding sites and ion identities from protein structures. Surface candidate sites are first pruned, followed by refinement of the most probable sites and metal types. This hierarchical strategy enables robust and accurate metal prediction for cryo‐EM and AlphaFold‐derived ...
Gangeun Park, Chaok Seok, Hahnbeom Park
wiley +1 more source
Bio-Inspired Enhanced Adaptive Centered Collision Optimizer for Hyperparameter Optimization of Multi-Scale Spatio-Temporal ConvNeXt in Boxing Action Recognition. [PDF]
Liu T.
europepmc +1 more source
Q‐LEAP: Millisecond Hyperdimensional Optimization for Full‐Spectrum Optical Metamaterials
Q‐LEAP integrates physics‐informed residual machine learning with factorization‐machine‐encoded quantum annealing to design full‐spectrum optical metamaterials. It explores a 2108 design space and, in a single 2.56 ms annealing step, reaches 85.83% of the theoretical FoM limit, enabling selective 5‐8 µm emission with 3–5 and 8–14 µm suppression and ∼40×
Zikang Guo +3 more
wiley +1 more source
BO-LSTM-Based TDE Precise Estimation Model of Capacitive MEMS-Gyros Using Thermal-Induced Physical Characteristics Variation Analysis. [PDF]
Qi B, Li P, Ding J, Jia C, Tian H.
europepmc +1 more source
An eight‐stream 2.5D Transformer integrates complementary PET metabolic and CT morphologic information to estimate spread‐through‐air‐spaces risk before surgery in lung adenocarcinoma. The model generalizes across independent centers, while its continuous risk score independently stratifies progression‐free survival, supporting further prospective ...
Xin‐Yu Zhu +7 more
wiley +1 more source
Diversity Beats Size Scaling for Chemical Language Models. [PDF]
Medina B +4 more
europepmc +1 more source
Flexible Integration of Structurally Diverse Spatial Multi‐Omics With AgaeSMO
AgaeSMO is a versatile and robust deep learning framework for flexible cross‐integration of spatial multi‐omics data. Leveraging a GATs network with a graph attention module, it learns joint embedding across diverse modalities, enabling integration of both structurally paired (e.g., spatial transcriptome‐epigenome, transcriptome‐proteome, transcriptome‐
Kunpeng Liu +9 more
wiley +1 more source
DRL-Based LEO Constellation Design for Regional Navigation Enhancement. [PDF]
Rui Z, Zeng F, Ouyang X, Chen L.
europepmc +1 more source
A new good point set stepwise shrinkage optimization in machine learning model for fog node performance prediction. [PDF]
Bo Z +6 more
europepmc +1 more source

