The confidence curve of a binary image. حسب Dingming Yang (8505990)

The confidence change of the binary image after iteration. حسب Dingming Yang (8505990)

Illustration of the transformed binary images of normal, benign, and malignant samples into grayscale. حسب Tehnan I. A. Mohamed (16846175)

Schematic representation of semi-automated algorithm for organoids analyzing. حسب Anna Demchenko (18449439)

Image1_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.TIF حسب Sizhuo Yu (11429743)

Image3_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.TIF حسب Sizhuo Yu (11429743)

Image2_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.TIF حسب Sizhuo Yu (11429743)

Generalized Tensor Decomposition With Features on Multiple Modes حسب Jiaxin Hu (1327875)

"…An efficient alternating optimization algorithm with provable spectral initialization is further developed. …"

Thesis-RAMIS-Figs_Slides حسب Felipe Santibañez-Leal (10967991)

"…<br><br>Finally, although the developed concepts, ideas and algorithms have been developed for inverse problems in geostatistics, the results are applicable to a wide range of disciplines where similar sampling problems need to be faced, included but not limited to design of communication networks, optimal integration and communication of swarms of robots and drones, remote sensing.…"

Flow diagram of the automatic animal detection and background reconstruction. حسب David Tadres (9120564)

"…If the identical blob that was detected in panel J (bottom) is found in any of the new subtracted binary images (cyan arrow), the animal is considered as having left its original position, and the algorithm continues. …"

Supplementary Material 8 حسب Nishitha R Kumar (19750617)

"…</li><li><b>XGboost: </b>An optimized gradient boosting algorithm that efficiently handles large genomic datasets, commonly used for high-accuracy predictions in <i>E. coli</i> classification.…"