The indispensability of lip reading has garnered paramount significance, propelled by the strides achieved in the realm of deep *** transformative paradigm shift not only heralds a commitment to enhanced communication...
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In today's competitive world, investigating students learning performance is the major component for accessing any educational systems, Predicting the students' performance in academics is a difficult task. In...
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ISBN:
(纸本)9798350349221
In today's competitive world, investigating students learning performance is the major component for accessing any educational systems, Predicting the students' performance in academics is a difficult task. In order to address this, researchers use the EDM (Educational Data Mining) technique to examine data from educational settings and enhance the educational system based on the collected data. This allows for a more accurate and comprehensive understanding of students' performance and helps them achieve better educational outcomes. Prediction of student performance in academics helps to analyze students community in better understandable and communicable with the wide range of socio demographic(age, gender, family, size, obesity, marital status of parents, occupation,),learning practices(school level), student related(stress and lifestyle) variables Numerous methods are employed to assess students' academic performance;however, the primary goal of this work is to build a prediction model through the application of machine learning techniques, such as logistic regression, K-Nearest Neighbor algorithm (KNN), and Support Vector Machine (SVM).Multiple approaches are used here to measure the performance of academics of students along with good prediction method based on accuracy. The predictive models offer valuable insights into the factors influencing academic success, allowing for the allocation of resources through social media and interventions more effectively. The prediction is a variable that helps to predict how many hours they spend on internet in some activities based on data collected. The result is a predictor variable that aids in forecasting academic achievement on the final exam of the semester (CGPA). The study identifies the lagged part of the studies and how it affect the education history in future. The results as the prediction have been increased which helps the institution and others in encouraging and help the students in different ways. The hea
Liver tumors rank as the third deadliest cancer globally and the sixth most prevalent disease worldwide. They primarily afflict individuals who frequently consume tobacco or alcohol. Approximately 75-85 percent of pri...
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Elections are crucial in India as they reflect the democratic principles that underpin the country's governance. Since the general elections in 2004, Electronic Voting Machines (EVMs) have been used in India. EVMs...
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Campus safety is a paramount concern in educational institutions worldwide, especially in combating the prevalence of campus violence. This comprehensive review utilizes advanced image processing and computer vision t...
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Efficient waste control is critical for India's smart cities. This study uses Convolutional Neural network (CNN) technology to classify and reveal waste, integrating sensors, Internet of Things (IoT) gadgets, and ...
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Creative work means doing work that has not been done or thought to date. It involves your logical and reasoning ability. It includes making creative efforts in sculpture, painting, sketching, etc. Creativity allows p...
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Forest fires are so dangerous to ecosystems, people, and property, precise prediction models are essential for developing effective mitigation measures. Convolutional Neural Networks (CNNs) constructed in TensorFlow a...
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Magnetic resonance imaging (MRI) has become a valuable diagnostic assessment means for the detection, segmentation, and characterization of brain tumors. However, low brightness and low contrast in MRI images pose a s...
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ISBN:
(纸本)9789819994410
Magnetic resonance imaging (MRI) has become a valuable diagnostic assessment means for the detection, segmentation, and characterization of brain tumors. However, low brightness and low contrast in MRI images pose a significant challenge for accurate tumor detection, especially in the early stages. Several approaches have been proposed to address this challenge, including image enhancement and filtering techniques. However, these methods often result in loss of image details, making it difficult to discern the tumor regions from the non-tumor ones. To overcome these limitations, deep learning-based approaches have gathered attention in recent years for their capability to automatically learn features from the input images and achieve high accuracy in various medical imaging tasks. The aim of our research is to present a deep learning-based methodology for detecting brain tumors in low-brightness and low-contrast MRI images. We employ a neural network with convolutions’ (CNN) architecture, which has been proven to be effective in acquiring complex image features. Previous studies have used deep learning techniques for brain tumor segmentation and detection (Ramin Ranjbarzadeh et al. in Brain tumor segmentation based on deep learning and an attention mechanism using MRI multi-modalities brain images [1]). However, these studies did not specifically address the problem of low brightness and low contrast in MRI images. In contrast, our proposed method is designed to capture the subtle differences between tumor regions and non-tumor regions in such MRI images. Our CNN model has been trained and validated on a larger dataset of MRI images, including both normal and tumor-containing images. Our results demonstrate that our proposed method achieves high accuracy and specificity in detecting brain tumors, even in low-brightness and low-contrast MRI images. Additionally, our method has the potential to aid healthcare professionals in precisely and promptly pronouncing tumors
Stuttering is a speech disorder accompanied by disruptions in the fluency of speaking and is characterized by involuntary repetitions, prolongations, or blocks in speech. The early detection and recommendation for per...
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