Essays about: "Skip-Connections"
Showing result 1 - 5 of 8 essays containing the word Skip-Connections.
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1. Generative Adversarial Networks in Lip-Synchronized Deepfakes for Personalized Video Messages
University essay from Lunds universitet/Matematik LTHAbstract : The recent progress of deep learning has enabled more powerful frameworks to create good-quality deepfakes. Deepfakes, which are mostly known for malicious purposes, have great potential to be useful in areas such as the movie industry, education, and personalized messaging. READ MORE
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2. Skip connection in a MLP network for Parkinson’s classification
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In this thesis, two different architecture designs of a Multi-Layer Perceptron network have been implemented. One architecture being an ordinary MLP, and in the other adding DenseNet inspired skip connections to an MLP architecture. READ MORE
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3. Design of 3D-printed cranioplasty moulds using Neural Network
University essay from Lunds universitet/Matematik LTHAbstract : Cranioplasty is surgical repair of a skull bone defect due to a previous surgery or injury. Cranioplasty is most often performed with autologous bone flap, i.e the patient's own saved bone from previous surgery if this is available. READ MORE
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4. Automation of Kidney Perfusion Analysis from Dynamic Phase-Contrast MRI using Deep Learning
University essay from KTH/Skolan för kemi, bioteknologi och hälsa (CBH)Abstract : Renal phase-contrast magnetic resonance imaging (PC-MRI) is an MRI modality where the phase component of the MR signal is made sensitive to the velocity of water molecules in the kidneys. PC-MRI is able to assess the Renal Blood Flow (RBF), which is an important biomarker in the development of kidney disease. READ MORE
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5. Semantic Segmentation of Urban Scene Images Using Recurrent Neural Networks
University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskapAbstract : Background: In Autonomous Driving Vehicles, the vehicle receives pixel-wise sensor data from RGB cameras, point-wise depth information from the cameras, and sensors data as input. The computer present inside the Autonomous Driving vehicle processes the input data and provides the desired output, such as steering angle, torque, and brake. READ MORE