Essays about: "Convolutional Neural Nets"
Showing result 1 - 5 of 6 essays containing the words Convolutional Neural Nets.
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1. Cell Identification from Microscopy Images using Deep Learning on Automatically Labeled Data
University essay from Lunds universitet/Institutionen för elektro- och informationsteknikAbstract : In biology, cell counting provides a fundamental metric for live-cell experiments. Unfortunately, most researchers are constrained to using tedious and invasive methods for counting cells. Automatic identification of cells in microscopy images would therefore be a valuable tool for such researchers. READ MORE
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2. Deep learning for nanofluidic scattering microscopy
University essay fromAbstract : A novel technique for label-free, real-time characterization of single biomolecules called Nanofluidic Scatter Microscopy (NSM) has recently been developed by a the Langhammer research group at Chalmers. We have created a machine learning (ML) framework consisting of deep convolutional neural networks such as U-nets, FCNNs, and YOLO in order to characterize single biomolecules through kymographs collected through NSM, as an alternative approach to a standard data analysis method (SA). READ MORE
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3. Image inpainting methods for elimination of non-anatomical objects in medical images
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This project studies the removal of non-anatomical objects from medical images. During tumor ablation procedures, the ablation probes appear in the image, hindering the performance of segmentation, registration, and dose computation algorithms. These algorithms can also be affected by artifacts and noise generated by body implants. READ MORE
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4. An evaluation of using a U-Net CNN with a random forest pre-screener : On a dataset of hand-drawn maps provided by länsstyrelsen i Jönköping
University essay from Högskolan i Skövde/Institutionen för informationsteknologiAbstract : Much research has been done on the use of machine learning to extract features such as buildings, lakes et cetera from satellite imagery, and while this dataset is valuable for many use cases, it is limited to time periods in which satellites were used. Historical maps have a much greater range of available time periods but the viability of using machine learning to extract data from these has not been investigated to any great extent. READ MORE
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5. Deep Neural Networks Based Disaggregation of Swedish Household Energy Consumption
University essay fromAbstract : Context: In recent years, households have been increasing energy consumption to very high levels, where it is no longer sustainable. There has been a dire need to find a way to use energy more sustainably due to the increase in the usage of energy consumption. READ MORE
