This study’s methodology aims to develop a sound NST process encompassing the basic phases of data preprocessing, model specification, estimation, and model assessment. The selected dataset applied here is MS-COCO, a large and versatile image…
Category: 7. Maths
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Optimization on multifractal loss landscapes explains a diverse range of geometrical and dynamical properties of deep learning
Multifractal loss landscape reproduces key properties found in realistic scenarios
We first introduce our model for deep neural network optimization. The capacity of a deep neural network \(f:{{\mathbb{R}}}^{{d}_{{{\rm{in}}}}}\to…
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A comparative study of deterministic and stochastic computational modeling approaches for analyzing and optimizing COVID-19 control
Existence of unique and global positive solution
In the following, we will demonstrate that the system (1) has a unique positive solution.
Theorem 1
For all \((S(0),V(0),I(0),R(0)) \in {\mathbb {R}}^{4}_{+}\), a…
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Bifurcation, chaos, modulation instability, and soliton analysis of the schrödinger equation with cubic nonlinearity
The study of many dynamical happenings in the real world, especially in the domains of chemical reactions1, plasma physics2, magnetohydrodynamics3, optical fibers4, fluid dynamics5, telecommunications6, quantum mechanics7, and other applications
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Federated deep reinforcement learning-based urban traffic signal optimal control
To validate the effectiveness of the proposed single-intersection signal control method based on federated PPO, this section presents a series of training and testing experiments conducted under various traffic flow scenarios. The experimental…
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Multi-scale adversarial diffusion network for image super-resolution
In this section, the datasets, training configuration, experimental environment and other relevant aspects used in the experiments are described in detail. Subsequently, the qualitative and quantitative results obtained from the two datasets are…
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Scale selection and machine learning based cell segmentation and tracking in time lapse microscopy
In this section we detail the two main components of our framework: cell segmentation and detection, and cell tracking.
Cell segmentation and detection
We display the main stages for cell segmentation and detection in Fig. 1. We describe each of…
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Advancing plant leaf disease detection integrating machine learning and deep learning
Figure 2 presents the detailed work of the proposed approach.
Fig.2 Fusion of DL and ML for Plant Leaf Disease Detection.
Dataset
In the present work, we have used 4 datasets23,24,25,26. Ref23 includes 408 original banana images from real fields of…
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Reversible data hiding and authentication scheme for encrypted image based on prediction error compression
In this section, we introduce the existing VRAE methods and RRBE methods.
VRAE
In the VRAE scheme, the image needs to be encrypted first and then the data is embedded. Puech et al. (2008)9 proposed one of the initial VRAE schemes, their method…
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Fractional-order computational modeling of pediculosis disease dynamics with predictor–corrector approach
It is well known that using numerical methods to solve ordinary differential equations is not suitable for solving differential equations of any order. We now discuss the PC approach, which is a generalization of the classical trapezoidal rule….
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