بدائل البحث:
process optimization » model optimization (توسيع البحث)
while optimization » whale optimization (توسيع البحث), wolf optimization (توسيع البحث), phase optimization (توسيع البحث)
waste process » waste processing (توسيع البحث), step process (توسيع البحث), whole process (توسيع البحث)
binary waste » binary data (توسيع البحث), binary mask (توسيع البحث)
size while » line while (توسيع البحث), cite while (توسيع البحث)
process optimization » model optimization (توسيع البحث)
while optimization » whale optimization (توسيع البحث), wolf optimization (توسيع البحث), phase optimization (توسيع البحث)
waste process » waste processing (توسيع البحث), step process (توسيع البحث), whole process (توسيع البحث)
binary waste » binary data (توسيع البحث), binary mask (توسيع البحث)
size while » line while (توسيع البحث), cite while (توسيع البحث)
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Flow diagram of the proposed model.
منشور في 2025"…<div><p>Machine learning models are increasingly applied to assisted reproductive technologies (ART), yet most studies rely on conventional algorithms with limited optimization. This proof-of-concept study investigates whether a hybrid Logistic Regression–Artificial Bee Colony (LR–ABC) framework can enhance predictive performance in in vitro fertilization (IVF) outcomes while producing interpretable, hypothesis-driven associations with nutritional and pharmaceutical supplement use. …"
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Data_Sheet_1_A Global Optimizer for Nanoclusters.PDF
منشور في 2019"…In this recursive algorithm, an n-sized cluster is built from the geometries of n−1 clusters. …"
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Data_Sheet_1_Posiform planting: generating QUBO instances for benchmarking.pdf
منشور في 2023"…<p>We are interested in benchmarking both quantum annealing and classical algorithms for minimizing quadratic unconstrained binary optimization (QUBO) problems. …"
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Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf
منشور في 2024"…Next, a hybrid feature extraction approach is presented leveraging transfer learning from selected deep neural network models, InceptionV3 and DenseNet201, to extract comprehensive feature sets. To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. …"
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Sample image for illustration.
منشور في 2024"…Additionally, we provide a solution to determine the optimal block size for describing nonlinear regions, thereby enhancing resolution. …"
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Comparison analysis of computation time.
منشور في 2024"…Additionally, we provide a solution to determine the optimal block size for describing nonlinear regions, thereby enhancing resolution. …"
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Process flow diagram of CBFD.
منشور في 2024"…Additionally, we provide a solution to determine the optimal block size for describing nonlinear regions, thereby enhancing resolution. …"
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Precision recall curve.
منشور في 2024"…Additionally, we provide a solution to determine the optimal block size for describing nonlinear regions, thereby enhancing resolution. …"
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Quadratic polynomial in 2D image plane.
منشور في 2024"…Additionally, we provide a solution to determine the optimal block size for describing nonlinear regions, thereby enhancing resolution. …"
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Thesis-RAMIS-Figs_Slides
منشور في 2024"…From the results obtained across these three real scenarios explored in this thesis, it is possible to see that the proposed methodology achieves better performances than sampling in a structured regular grid (used as a conventional rule for sampling) in terms of both error in image reconstruction and global economic value, when considering the economic revenue of processing the ore and dumping the waste. <br><br>It is important to emphasize that no previous work have addressed the optimal sensing problem covered in this thesis for characterization of geological fields in the context of \emph{<i>MPS</i>}. …"
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Image1_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.TIF
منشور في 2021"…Its current hardware implementation relies on D-Wave’s Quantum Processing Units, which are limited in terms of number of qubits and architecture while being restricted to solving quadratic unconstrained binary optimization (QUBO) problems. …"
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Image3_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.TIF
منشور في 2021"…Its current hardware implementation relies on D-Wave’s Quantum Processing Units, which are limited in terms of number of qubits and architecture while being restricted to solving quadratic unconstrained binary optimization (QUBO) problems. …"
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Image2_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.TIF
منشور في 2021"…Its current hardware implementation relies on D-Wave’s Quantum Processing Units, which are limited in terms of number of qubits and architecture while being restricted to solving quadratic unconstrained binary optimization (QUBO) problems. …"
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DataSheet1_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.pdf
منشور في 2021"…Its current hardware implementation relies on D-Wave’s Quantum Processing Units, which are limited in terms of number of qubits and architecture while being restricted to solving quadratic unconstrained binary optimization (QUBO) problems. …"
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PathOlOgics_RBCs Python Scripts.zip
منشور في 2023"…No segmented cell(s) occupied a space larger than 80x80 pixels, including the three-overlapping RBCs. As a result, the algorithm centred/padded each cell(s) within an 80x80 pixel-sized image, generating mask, cropped, and segmented images, all following a standardized naming convention that begins with the slide/smear number, followed by the patch number, and concludes with the (XYWH) coordinates. …"