The web applications security systems often use the authentication strategy and credentials to assess the identity of the user. Based on the credentials, the system is able to claim the identity of the user. Also, the...
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The field of Optical Character Recognition (OCR) consists of techniques that are mainly focused on document image analysis. Aside from generating significant speedups of everyday procedures, OCR has a considerable rol...
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Cybersecurity has in recent years emerged as a paramount concern in the design and operation of industrial systems and civil infrastructures, due mainly to their susceptibility to malicious cyber attacks which take ad...
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The market of Medical Devices has an annual growth rate perspective of 5.4% in the 2022 - 2028 period. The growth rate is mainly supported by the increased usage of devices for chronic diseases prevention and for remo...
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Longer training times pose a significant challenge in Artificial neural networks (ANNs) as it may leads to increasing the computational costs and decreasing the effectiveness of the model. Therefore, it is imperative ...
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Longer training times pose a significant challenge in Artificial neural networks (ANNs) as it may leads to increasing the computational costs and decreasing the effectiveness of the model. Therefore, it is imperative to reduce training times in ANNs to enhance the computational efficiency. The initialization of the weights between the layers in ANN plays a vital role in reducing training times. Appropriate weight initialization can help the network converge faster during the training by providing an optimum starting point for the network. Therefore, weight initialization techniques are essential for efficient training of ANNs. This paper revisits and implements different popular weight initialization techniques in ANNs and analyzes their impact on training time. Specifically, this paper implements Gaussian-based, Kaming-based, and Xavier-based weight initiation atop a popular DNN-based network. The experiments are conducted by employing a well-known dataset. The results show that the scenario when no weight initiation is applied consumed the highest training time, whereas different weight initiation techniques contribute in reducing the training times for the network.
Evaluation is a process that compares the results with the target, an initial situation with the final one. ‘Evaluate’ means making an assessment based on some measure or information and referring to some criteria. ...
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Nowadays, information and knowledge represent the fundamental wealth of an organisation. Enterprises try to utilise this wealth to gain advantage when making decisions such as a project’s acceptance. After a project ...
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Existing explainability approaches for convolutional neural networks (CNNs) are mainly applied after training (post-hoc) which is generally unreliable. Ante-hoc explainers trained simultaneously with the CNN are more ...
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Data is information or a collection of information about something. Almost every application nowadays needs to persist data so that they can keep track of their state in case of any trouble that might appear. Database...
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Databases are the fundamental component of an application for storing data. SQL (Structured Query Language) is a query language that is used to create, read, update, and remove records in most relational databases (CR...
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