Essays about: "information processing style"
Showing result 1 - 5 of 12 essays containing the words information processing style.
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1. Image Colorization Based on Deep Learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : With the development of artificial intelligence, there is a clear trend to combine computer technology with traditional industries. In recent years, with the development of digital media technology, many methods for coloring gray-scale images have been proposed. READ MORE
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2. Vehicle Usage Modelling Under Different Contexts
University essay from Högskolan i Halmstad/Akademin för informationsteknologiAbstract : Modern vehicles nowadays are equipped with highly sensitive sensors which continuously log in the information when the vehicle is in motion. These vehicles also deal with some performance issues like more fuel consumption, breakdown, or failure, etc. READ MORE
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3. Cascade Mask R-CNN and Keypoint Detection used in Floorplan Parsing
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : Parsing floorplans have been a problem in automatic document analysis for long and have up until recent years been approached with algorithmic methods. With the rise of convolutional neural networks (CNN), this problem too has seen an upswing in performance. READ MORE
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4. Automatic Gait Recognition : using deep metric learning
University essay from Linköpings universitet/DatorseendeAbstract : Recent improvements in pose estimation has opened up the possibility of new areas of application. One of them is gait recognition, the task of identifying persons based on their unique style of walking, which is increasingly being recognized as an important method of biometric indentification. READ MORE
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5. Attention Mechanisms for Transition-based Dependency Parsing
University essay from Uppsala universitet/Institutionen för lingvistik och filologiAbstract : Transition-based dependency parsing is known to compute the syntactic structure of a sentence efficiently, but is less accurate to predict long-distance relations between tokens as it lacks global information about the sentence. Our main contribution is the integration of attention mechanisms to replace the static token selection with a dynamic approach that takes the complete sequence into account. READ MORE