Essays about: "Deep Neural Network"

Showing result 36 - 40 of 885 essays containing the words Deep Neural Network.

  1. 36. Towards gradient faithfulness and beyond

    University essay from Högskolan i Halmstad/Akademin för informationsteknologi

    Author : Vincenzo Buono; Isak Åkesson; [2023]
    Keywords : XAI; Visual Explanations; CAM; Grad-CAM; Expected Grad-CAM; Hyper Expected Grad; Class Activation Maps; Explainable AI; Faithfulness; Neural Network interpretability; Hyper Resolution CAM; Super Resolution CAM; Natural Encoding;

    Abstract : The riveting interplay of industrialization, informalization, and exponential technological growth of recent years has shifted the attention from classical machine learning techniques to more sophisticated deep learning approaches; yet its intrinsic black-box nature has been impeding its widespread adoption in transparency-critical operations. In this rapidly evolving landscape, where the symbiotic relationship between research and practical applications has never been more interwoven, the contribution of this paper is twofold: advancing gradient faithfulness of CAM methods and exploring new frontiers beyond it. READ MORE

  3. 37. Automated Interpretation of Lung Ultrasound for COVID-19 and Tuberculosis diagnosis

    University essay from Lunds universitet/Matematik LTH

    Author : Chloé Soormally; [2023]
    Keywords : Tuberculosis; COVID-19; Lung Ultrasound; Computer-aided detection CAD ; Deep learning; Technology and Engineering;

    Abstract : BACKGROUND. Early and accurate detection of infectious respiratory diseases like COVID-19 and tuberculosis (TB) plays a crucial role in effective management and the reduction of preventable mortality. READ MORE

  4. 38. Artificial Neural Networks for Financial Time Series Prediction

    University essay from Stockholms universitet/Institutionen för data- och systemvetenskap

    Author : Dana Malas; [2023]
    Keywords : artificial neural networks; time series analysis; deep learning; finance; long short-term memory; simple moving average;

    Abstract : Financial market forecasting is a challenging and complex task due to the sensitivity of the market to various factors such as political, economic, and social factors. However, recent advances in machine learning and computation technology have led to an increased interest in using deep learning for forecasting financial data. READ MORE

  5. 39. Finding the QRS Complex in a Sampled ECG Signal Using AI Methods

    University essay from KTH/Fysik

    Author : Jeanette Marie Victoria Skeppland Hole; [2023]
    Keywords : ECG; ECG-analysis; QRS detector; Artificial Intelligence; Machine Learning; Deep neural networks; Long short-term memory; Convolutional neural network; Multilayer perceptron; EKG; EKG-analys; QRS detektor; Artificiell intelligens; Maskininlärning; Djupa neurala nätverk; Long short-term memory; Convolutional neural network; Multilayer perceptron;

    Abstract : This study aimed to explore the application of artificial intelligence (AI) and machine learning (ML) techniques in implementing a QRS detector forambulatory electrocardiography (ECG) monitoring devices. Three ML models, namely long short-term memory (LSTM), convolutional neural network (CNN), and multilayer perceptron (MLP), were compared and evaluated using the MIT-BIH arrhythmia database (MITDB) and the MIT-BIH noise stress test database (NSTDB). READ MORE

  6. 40. Convolution-compacted visiontransformers forprediction of localwall heat flux atmultiple Prandtlnumbers in turbulentchannel flow

    University essay from KTH/Skolan för teknikvetenskap (SCI)

    Author : Yuning Wang; [2023]
    Keywords : Turbulent flow; Heat transfer; Vision transformer; Convolutional neural network; Machine learning;

    Abstract : Predicting wall heat flux accurately in wall-bounded turbulent flows is critical for a variety of engineering applications, including thermal management systems and energy-efficient designs. Traditional methods, which rely on expensive numerical simulations, are hampered by increasing complexity and extremly high computation cost. READ MORE