PPT-Learning Features and Parts for Fine-Grained Recognition

Authors Jonathan Krause Timnit Gebru Jia Deng Li Jia Li Li FeiFei ICPR 2014 Presented by Paritosh 1 Problem addressed Authors address the problem of FineGrained Recognition. Liwen. Sun, Michael J. Franklin, Sanjay Krishnan, Reynold S. . Xin†. UC . Berkeley and †. Databricks. Inc. .. VLDB 2014. March 17, 2015. Heymo. Kou. Introduction. Overview. Workload Analysis. The Partitioning Problem. Xen. Bhanu Vattikonda. with . Sambit. Das and . Hovav. . Shacham. 2. Motivation . Project goals. Goals of the paper. Discussion . Future work. Motivation. 3. Recent research efforts have shown that covert channel attacks are possible in the cloud using fine grained timers . Recognition tasks. Machine learning approach: training, testing, generalization. Example classifiers. Nearest neighbor. Linear classifiers. Image features. Spatial support:. Pixel or local patch. Segmentation region. Andréia Marini . Adviser: Alessandro L. . Koerich. Postgraduate . Program in Computer Science (. PPGIa. ) . Pontifical . Catholic University of . Paraná (PUCPR). Outline. Motivation. The . Challenge. Zechao Shang. 1. , . Feifei. Li. 2. , Jeffrey Xu Yu. 1. Zhiwei. Zhang. 3. , Hong Cheng. 1. . 1. The Chinese University of Hong Kong. . 2. University of Utah. 3. Hong Kong Baptist University. not. Recognition(. 细粒度分类. ) . 沈志强. Datasets. . -- Caltech-UCSD Bird-200-2011. Number of categories: 200. Number of images: 11,788. Annotations per image: 15 Part Locations, 1 Bounding Box. Factors Affecting Reliable Word Sense Annotation. Susan . Windisch. Brown, Travis Rood, and Martha Palmer. University of Colorado at Boulder. Annotators in their little nests agree;. And ‘tis a shameful sight,. . NFs. . for. . Flexiable. . per-flow. . Customization. Wei Zhang, Jinho Hwang, Shriram Rajagopal, k.k. . ramakrishnan. and . timothy. . wood. – conext 2016. From: Class Wide Monolithic NFs . Deep Learning for Expression Recognition in Image Sequences Daniel Natanael García Zapata Tutors: Dr. Sergio Escalera Dr. Gholamreza Anbarjafari April 27 2018 Introduction and Goals Introduction Dennis Hamester et al., “Face ExpressionRecognition with a 2-Channel ConvolutionalNeural Network”, International Joint Conference on Neural Networks (IJCNN), 2015. Joel Kamdem Teto. z. Introduction. Fine-grained Multithreading . The ability of a single core to handle multiple thread by:. Providing a register for each thread. Dividing the pipeline bandwidth into N part . Lijie. Chen. MIT. Today’s Topic. Background. . What is Fine-Grained Complexity?. The Methodology of Fine-Grained Complexity. Frontier: Fine-Grained Hardness for Approximation Problems. The Connection. Andréia Marini . Adviser: Alessandro L. . Koerich. Postgraduate . Program in Computer Science (. PPGIa. ) . Pontifical . Catholic University of . Paraná (PUCPR). Outline. Motivation. The . Challenge. Heng. . Ji (UIUC. ). 1. What are “entities”?. [Main meaning]. - unique world bodies with (non-unique) names, such as. people, organizations, locations. e.g. . Washington County. [Extended meaning – information extraction]. Krossfjord. and . Fensfjord. formations, Troll Field, northern North Sea. Richard Brown. Tectonic Location. Located on the . Horda. Platform. This is on the eastern margin of the Viking . Graben.