Browsing Computer Science Masters Papers by Subject "Neural networks (Computer science)"

Now showing items 1-8 of 8

    • Brain Cancer Detection Using MRI Scans 

      Thotapally, Shanthanreddy (North Dakota State University, 2020)
      An estimate of about 700,000 Americans today live with a brain tumor. Of these, 70% are benign and 30% are malicious. The average survival rate of all the malicious brain tumor patients is 35%. Diagnosing these tumors early ...

    • Comparison of RNN, LSTM and GRU on Speech Recognition Data 

      Shewalkar, Apeksha Nagesh (North Dakota State University, 2018)
      Deep Learning [DL] provides an efficient way to train Deep Neural Networks [DNN]. DDNs when used for end-to-end Automatic Speech Recognition [ASR] tasks, could produce more accurate results compared to traditional ASR. ...

    • Electricity Demand Prediction Using Artificial Neural Network Framework 

      Param, Sowjanya (North Dakota State University, 2015)
      As the economy is growing, electricity usage has been growing and to meet the needs of energy market in providing the electricity without power outages, utility companies, distributors and investors need a powerful tool ...

    • Image Classification Using Transfer Learning and Convolution Neural Networks 

      Burugupalli, Mohan (North Dakota State University, 2020)
      In the recent years, deep learning has shown to have a formidable impact on image classification and has bolstered the advances in machine learning research. The scope of image recognition is going to bring big changes in ...

    • Implementation of Weighted Centroid Neural Network for Edge Preserving Image Compression 

      Depa, Amarender Reddy (North Dakota State University, 2017)
      Image compression is a type of data compression applied to images. The objective of image compression is to reduce the cost for storage or transmission. Image compression is associated with removing redundant information ...

    • Object Classification Using Stacked Autoencoder and Convolutional Neural Network 

      Gottimukkula, Vijaya Chander Rao (North Dakota State University, 2016)
      In the recent years, deep learning has shown to have a formidable impact on object classification and has bolstered the advances in machine learning research. Many image datasets such as MNIST, CIFAR-10, SVHN, Imagenet, ...

    • Predictive Performance Evaluation of Different Neural Networks Using Stock Prices 

      Nyavanandi, Deepika (North Dakota State University, 2019)
      Forecasting stock market prices has been a challenging task due to its volatile nature and nonlinearity. Recently, artificial neural networks (ANNs) have become popular in solving a variety of scientific and financial ...

    • Stock Price Prediction Using Recurrent Neural Networks 

      Jahan, Israt (North Dakota State University, 2018)
      The stock market is generally very unpredictable in nature. There are many factors that might be responsible to determine the price of a particular stock such as the market trend, supply and demand ratio, global economy, ...