To address the shortcomings of classical chaotic time series in image encryption algorithms in terms of low complexity, fewer control parameters, and limited range of value domains, this paper ...

Automatic Optimization of One-Dimensional CNN Architecture for Fault Diagnosis of a Hydraulic Piston Pump Using Genetic Algorithm ...

This study aims to classify the level of agricultural soil fertility based on texture. This study proposes a new approach to categorizing soil fertility levels based on soil texture using the ...

The traditional manual settlement method is characterized by low efficiency, high labor and resource consumption, and significant negative impact on consumers' shopping experience. To effectively ...

Deep learning algorithms have started to show impressive results in the segmentation of brain tumors from MRI images over recent years. Therefore, this study presents a new deep learning algorithm ...

To reduce multiplication operations in convolution of convolutional neural networks (CNNs), there are three widely used convolutional acceleration algorithms, i.e., Winograd, FFT and FFA. However, ...

The efficient and accurate detection of cracks in concrete structures is critical for maintaining structural integrity and safety. This study compares two state-of-the-art convolutional neural network ...

To address the problems of relying on electronic repositories and being vulnerable to network influence in obtaining key information of literature in mainstream literature management software, an ...

This paper proposes an automatic region-based layout optimization method for substation main wiring diagrams using a improved genetic algorithm. The method addresses the problems of low space ...

Unfortunately, by analyzing their robustness using gradient-based algorithms, several studies have shown that some of these malware detectors are vulnerable to the evasion attacks (also known as ...

Vehicle classification and accident avoidance in hill stations is an important problem that can be solved using computer vision techniques and machine learning algorithms. The proposed system consists ...