Results 1 - 10 of 64

Learning mid-level features for recognition

by Y-lan Boureau, Francis Bach, Yann LeCun, Jean Ponce , 2010
"... Many successful models for scene or object recognition transform low-level descriptors (such as Gabor filter responses, or SIFT descriptors) into richer representations of intermediate complexity. This process can often be broken down into two steps: (1) a coding step, which performs a pointwise tra ..."
Abstract - Cited by 228 (13 self) - Add to MetaCart
shared by modern mid-level feature extractors, our approach aims to facilitate the design of better recognition architectures.

Learning Mid-Level Features and Modeling Neuron Selectivity for Image Classification

by Shu Kong, Zhuolin Jiang, Qiang Yang
"... We now know that mid-level features can greatly enhance the performance of image learning, but how to automatically learn the image features ef-ficiently and in an unsupervised manner is still an open question. In this paper, we present a very ef-ficient mid-level feature learning approach (Mid-Fea) ..."
Abstract - Add to MetaCart
We now know that mid-level features can greatly enhance the performance of image learning, but how to automatically learn the image features ef-ficiently and in an unsupervised manner is still an open question. In this paper, we present a very ef-ficient mid-level feature learning approach (Mid

Leveraging Mid-Level Semantic Boundary Cues for Automated Lymph Node Detection

by Ari Seff, Le Lu, Adrian Barbu, Holger Roth, Hoo-chang Shin, Ronald M. Summers
"... Abstract. Histograms of oriented gradients (HOG) are widely employed image descriptors in modern computer-aided diagnosis systems. Built upon a set of local, robust statistics of low-level image gradients, HOG features are usually computed on raw intensity images. In this paper, we explore a learned ..."
Abstract - Add to MetaCart
learned image transformation scheme for producing higher-level inputs to HOG. Leveraging semantic object boundary cues, our methods compute data-driven image feature maps via a supervised boundary detector. Compared with the raw image map, boundary cues offer mid-level, more object-specific visual

Feature-Based Reconstruction of 3D Primitives from Multiple Views

by Joachim Bauer, Prof Dr, Franz Leberl , 2009
"... The modeling i.e. the capturing of geometric information plays a key role for our fast growing urban communities. Until recently the process of capturing three-dimensional data was a labor intensive task, but with the advent of high resolution digital imaging instruments a high degree of automation ..."
Abstract - Add to MetaCart
of mid-level features such as ellipses and 2D line segments and new efficient methods for extracting 3D primitives from 2D features. The main contributions of this work are methods for extracting vanishing points, robust fitting of regular polygons, a method for the efficient matching of points

Connecting TCAD To Tapeout A Journal for CAD/CAE Engineers

by unknown authors
"... Maverick is a modern hierarchical netlist extractor, providing extraordinary effi ciency as well as comprehensive features and ease of use. It runs on PC under Microsoft Windows NT providing unique productivity in ..."
Abstract - Add to MetaCart
Maverick is a modern hierarchical netlist extractor, providing extraordinary effi ciency as well as comprehensive features and ease of use. It runs on PC under Microsoft Windows NT providing unique productivity in

Organizations and movements.

by Doug Mcadam , W Richard Scott - In Social Movements and Organization , 2005
"... Introduction There is little question that two of the most active and creative arenas of scholarly activity in the social sciences during the past four decades have been organizational studies (OS) and social movement analysis (SM). Both have been intellectually lively and vigorous in spite of the ..."
Abstract - Cited by 49 (0 self) - Add to MetaCart
phenomena." (Morris 2000, p. 445) OS began to gain traction with the recognition of the importance of the wider environment, first material resource and technical features, then political, and, more recently, institutional and cultural forces. Open systems conceptions breathed new life into a field

feature em A Summary of the 2008 Critical Review Prospects for Future Climate Change and the Reasons for Early Action

by Michael C. Maccracken
"... Combustion of coal, oil, and natural gas and, to a lesser extent, deforestation, landcover change, and emissions of halocarbons and other greenhouse gases (GHGs), are rapidly increasing the atmospheric concentrations of climate-warming gases. Past emissions have initiated warming of 0.1–0.2 °C per d ..."
Abstract - Add to MetaCart
, and present atmospheric levels of GHGs will contribute to a further warming of 0.5–1.0 °C, as equilibrium is re-established. Warming has been and will be greater in mid and high latitudes compared to low latitudes, over land compared to oceans, and at night compared to day. As emissions continue to increase

Practical aggregation of semantical program properties for machine learning based optimization

by Mircea Namolaru, Albert Cohen, Grigori Fursin, Ayal Zaks, Ari Freund - In Intl. Conf. on Compilers Architectures and Synthesis for Embedded Systems (CASES’10 , 2010
"... Iterative search combined with machine learning is a promising approach to design optimizing compilers harnessing the complexity of modern computing systems. While traversing a program optimization space, we collect characteristic feature vectors of the program, and use them to discover correlations ..."
Abstract - Cited by 4 (2 self) - Add to MetaCart
Iterative search combined with machine learning is a promising approach to design optimizing compilers harnessing the complexity of modern computing systems. While traversing a program optimization space, we collect characteristic feature vectors of the program, and use them to discover

Author manuscript, published in "International Conference on Compilers Architectures and Synthesis for Embedded Systems (CASES'10) (2010)" Practical Aggregation of Semantical Program Properties for Machine Learning Based Optimization

by Mircea Namolaru, Albert Cohen, Grigori Fursin, Ayal Zaks, Ari Freund , 2011
"... Iterative search combined with machine learning is a promising approach to design optimizing compilers harnessing the complexity of modern computing systems. While traversing a program optimization space, we collect characteristic feature vectors of the program, and use them to discover correlations ..."
Abstract - Add to MetaCart
Iterative search combined with machine learning is a promising approach to design optimizing compilers harnessing the complexity of modern computing systems. While traversing a program optimization space, we collect characteristic feature vectors of the program, and use them to discover

AN EXPLORATION OF MULTIMODAL DOCUMENT CLASSIFICATION STRATEGIES

by Scott Deeann Chen , 2011
"... This thesis explores multimodal document classification algorithms in a unified framework. Classification algorithms are designed to exploit both text and image information, which proliferates in modern documents. We design meta-classification schemes that combine and integrate state-of-the-art text ..."
Abstract - Add to MetaCart
-of-the-art text and image feature-extractors with state-of-the-art classifiers. Meta-classifiers fuse information across modalities that differ in nature and hence have more information on hand to make decisions. This thesis also discusses strategies that exploit correlations not only within a single modality
Results 1 - 10 of 64