Image inpainting consists of filling holes or missing parts of an image. Inpainting face images with symmetric characteristics is more challenging than inpainting a natural scene. None of the powerful existing models ...
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Run-time monitoring has been one of the widely used techniques to realize robust smart contracts. In this paper, we show how we can abstract aspects of run-time monitoring through declarations of programming languages...
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Traditional home security systems often face limitations in effectively addressing evolving security threats, such as theft and intrusion. These systems typically rely on conventional sensors and surveillance techniqu...
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The increased use of modern printing and scanning technologies has led to a significant rise in counterfeit currency production, posing a serious threat to global economies. To tackle this growing issue, our project, ...
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ISBN:
(纸本)9798350370249
The increased use of modern printing and scanning technologies has led to a significant rise in counterfeit currency production, posing a serious threat to global economies. To tackle this growing issue, our project, titled "Fake currency detection using Convolutional Neural Networks and Image Processing," introduces an innovative solution that utilizes artificial intelligence (AI) and machine learning for efficient counterfeit detection. Financial institutions, banks, and businesses are facing heightened vulnerability to counterfeit currency, resulting in considerable financial losses and a decrease in the value of genuine money. Current currency detection systems often rely on time-consuming traditional methods and manual inspection, which are prone to human error. Even the counterfeit detection machines in use have limitations when it comes to identifying sophisticated counterfeit notes. Our project addresses these challenges by proposing an advanced system that integrates convolutional neural networks (CNNs) and image processing techniques. Given the advancements in printing and scanning technologies, counterfeiting has evolved into a more sophisticated and widespread problem. Traditional currency detection methods, rooted in hardware and image processing, have proven to be inefficient and time-consuming. Hence, there is a critical need for a more robust and rapid solution to detect counterfeit currency. Our proposed approach employs a transfer-learned CNN, a deep learning model trained on a dataset comprising real and fake currency images. The CNN learns the intricate features of both genuine and counterfeit banknotes, allowing it to accurately identify fake currency in real-time. The transfer learning process enables the CNN to leverage knowledge gained from a diverse dataset, improving its ability to recognize subtle patterns associated with counterfeit notes. The primary components of our project include a diverse dataset with images of real and fake currenc
Fraud detection in smart grids is critical to ensure reliable and efficient energy distribution, preventing significant financial losses and maintaining grid stability. This project presents an advanced fraud detectio...
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Video deblurring is a fundamental problem in low-level vision, and many methods have employed designs based on CNNs and transformers. Traditional CNNs often require deeper architectures to achieve a larger receptive f...
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This paper presents models to differentiate between human-written and AI-generated essays, addressing challenges posed by advanced AI models like ChatGPT and Claude. Using a structured dataset, we fine-tune multiple m...
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Recognizing social cues and emotions is vital for navigating daily interactions, understanding emotions in conversations, interpreting body language in meetings, and supporting friends in difficult situations. This wo...
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Polycystic Ovary Syndrome (PCOS) is a complex endocrine illness that affects women of reproductive age. It is characterized by hormonal imbalance and ovarian malfunction. Its reasons are numerous, including genetic su...
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In this work, we address the strategic placement and optimal sizing of electric vehicle charging stations for cities as well as highway traffic to minimize overall cost. We formulate the problem as a Mixed Integer Lin...
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