PPT-kNN algorithm and CNN data reduction

MA4102 Data Mining and Neural Networks Nathan Ifill ngi1leacuk University of Leicester Image source Antti Ajanki Example of knearest neighbor classification 28 May 2007. Roselyn. . Sands. Thomas . McCabe. 1. Context van de opdracht. 2. (. Remember. Darwin?). Survival. of the . Fittest. :. How « fit » are . you. ?. Do . you. « . work. smart »:. Right . person. Yunchao. Wei, Wei Xia, . Junshi. Huang, . Bingbing. Ni, Jian Dong, Yao Zhao, Senior Member, IEEE . Shuicheng. Yan, Senior Member, IEEE. 2014. . arXiv. IEEE. . Short Papers. . HCPIssue. Date: Sept. 1 2016. kNN. tree-list imputation strategy for prediction of diameter densities from lidar. Jacob L . Strunk. Jacob.Strunk@oregonstate.edu. Nov 15, 2013. Note. “Diameter Density” in this context is referring to the . Tzachi. . Hershkovich. Image Quality – Degradation sources. Full Reference-Image Quality Assessment vs. No . Reference-Image Quality Assessment. System architecture. Training. Evaluation and results. Bharath. . Hariharan. , Pablo . Arbeláez. , . Ross . Girshick. and Jitendra Malik. UC . Berkeley. What is image understanding?. person 1. person 2. horse 1. horse 2. Object Detection. Detect every instance of the category and localize it with a bounding box.. Munif. CNN. The (CNN. ) . consists of: . . Convolutional layers. Subsampling Layers. Fully . connected . layers. Has achieved state-of-the-art result for the recognition of handwritten digits. Neural . Xueying. Bai, . Jiankun. Xu. Multi-label Image Classification. Co-occurrence dependency. Higher-order correlation: one label can be predicted using the previous label. Semantic redundancy: labels have overlapping meanings (cat and kitten). Deep Learning Architectures. feed-forward . networks. auto-encoders (output want to recover input image, middle layer smaller - use results of middle layer for compression. ). recurrent neural networks (RNNs) (backward feeding at run time as part of input into middle . &. Summarizing CNN Student News. Sections of your student binder. How I expect you to divide up the binder and label your sections.. This is important so that YOU can find material for review and I can find your assignments to grade.. CNN 10. August 4, 2018. Landmark Museum Lost. U.S. Supreme Court Confirmation Hearings . School Water Fountains Shut Off . Positive Athlete Shows Exceptional Perseverance. Make Up Day. September 4, 2018. 12/8/16. BGU, DNN course 2016. Sources. Main paper. “. Rich . feature hierarchies for accurate object detection and semantic . segmentation. ”, . Ross . Girshick. , Jeff Donahue, Trevor Darrell, . September 10, 2018. North Korean Parade. Mice, Ticks, and Lyme Disease. CNN 10. September 11. CNN 10. September 12, 2018 . Why Hurricane Florence is Uniquely Dangerous. CNN Hero Helps Children Worldwide. . for Robust Object Detection. Jiankang. Deng, . Shaoli. Huang, Jing Yang, . Hui. . Shuai. , . Zhengbo. Yu, . Zongguang. Lu, . Qiang. Ma, . Yali. Du, . Yi Wu. , . Qingshan. Liu, . Dacheng. Tao. Gowtham . Atluri. Mike Sokoloff. PV finder. LHCb. upgrade. Much higher pileup. Need for faster algorithms. Goal: Discovering PVs and SVs. Use of ML approaches. Transform 3D data to 1D. 1D Convolutional neural nets.