Residual Neural Networks Final Year Projects with Source Code
Residual Neural Networks Final Year Projects for BE, BTech, ME, MSc, MCA and MTech final year engineering students. These Residual Neural Networks projects give practical experience and help complete final-year submissions. All projects follow IEEE standards and each project includes source code, project thesis report, presentation, project execution and explanation.
Residual Neural Networks Final Year Projects
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Classification of Hemorrhage Using Priori Information of Electrode Arrangement With Electrical Impedance Tomography
This project focuses on detecting brain diseases using electrical impedance tomography, even when electrodes cannot be evenly placed. The researchers developed new ways to arrange electrodes and a smart method that considers these arrangements to locate brain bleeding accurately. Their approach was tested under many challenging conditions and showed very high accuracy and reliability. It performs better than traditional neural network methods for this task. -
Recurrent Residual Networks Contain Stronger Lottery Tickets
This project shows that large neural networks can be simplified without training by selecting smaller subnetworks from them. These small networks are sparse, use fewer values, and can run efficiently on hardware. The study finds that converting some networks into recurrent forms improves accuracy and reduces memory use. Using this method, a popular network can be shrunk almost 50 times while keeping good performance.
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Residual Neural Networks Project Synopsis & Presentation
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