전체 글
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Video-to-Video Synthesis카테고리 없음 2020. 8. 3. 13:03
https://arxiv.org/abs/1808.06601 Video-to-Video Synthesis We study the problem of video-to-video synthesis, whose goal is to learn a mapping function from an input source video (e.g., a sequence of semantic segmentation masks) to an output photorealistic video that precisely depicts the content of the source vide arxiv.org abstract 비디오 - 비디오 합성에 대한 문제를 연구한다. 기존 비디오의 내용을 정확하게 묘사하여 사질적인 비디오로 만드는 것..
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Enhanced Cognitive Walkthrough: Development of the Cognitive Walkthrough Method to Better Predict, Identify, and Present Usability Problems카테고리 없음 2020. 6. 2. 10:45
https://www.researchgate.net/publication/258400466_Enhanced_Cognitive_Walkthrough_Development_of_the_Cognitive_Walkthrough_Method_to_Better_Predict_Identify_and_Present_Usability_Problems (PDF) Enhanced Cognitive Walkthrough: Development of the Cognitive Walkthrough Method to Better Predict, Identify, and Present U PDF | To avoid use errors when handling medical equipment, it is important to dev..
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EfficientNet: Rethinking Model Scaling for Convolutional Neural NetworksARXIV/Convolution Neural Network 2020. 5. 13. 17:13
https://arxiv.org/abs/1905.11946v3 EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks Convolutional Neural Networks (ConvNets) are commonly developed at a fixed resource budget, and then scaled up for better accuracy if more resources are available. In this paper, we systematically study model scaling and identify that carefully balancing n arxiv.org abstract CNN의 경우 제한된 자원..
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Focal Loss for Dense Object DetectionARXIV/Convolution Neural Network 2020. 5. 4. 20:40
https://arxiv.org/abs/1708.02002 Focal Loss for Dense Object Detection The highest accuracy object detectors to date are based on a two-stage approach popularized by R-CNN, where a classifier is applied to a sparse set of candidate object locations. In contrast, one-stage detectors that are applied over a regular, dense sampl arxiv.org abstract 높은 정확도의 object detector는 two stage 방법으로 부족한 객체에 대한 ..
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CoroNet: A Deep Neural Network for Detection and Diagnosis of Covid-19 from Chest X-ray ImagesARXIV/Convolution Neural Network 2020. 4. 16. 11:58
https://arxiv.org/abs/2004.04931v2 CoroNet: A Deep Neural Network for Detection and Diagnosis of Covid-19 from Chest X-ray Images The novel Coronavirus also called Covid-19 originated in Wuhan, China in December 2019 and has now spread across the world. It has so far infected around 1.8 million people and claimed approximately 114698 lives overall. As the number of cases are rapidly arxiv.org ab..