'Linear support vector machine' presentation slideshows

Support Vector Machines

Support Vector Machines . Adapted from Lectures by Raymond Mooney (UT Austin) and Andrew Moore (CMU). Text classification. Earlier: Algorithms for text classification K Nearest Neighbor classification Simple, expensive at test time, low bias, high variance, non-linear

992 views • 64 slides

776 Computer Vision

776 Computer Vision. Face/Object detection. Jan-Michael Frahm, Enrique Dunn Spring 2013. Previous Lecture. The Viola/Jones Face Detector A seminal approach to real-time object detection Training is slow, but detection is very fast Key ideas Integral images for fast feature evaluation

751 views • 57 slides

CS276: Information Retrieval and Web Search Christopher Manning and Pandu Nayak

CS276: Information Retrieval and Web Search Christopher Manning and Pandu Nayak Lecture 13: Support vector machines and machine learning on documents. [Borrows slides from Ray Mooney]. Text classification. Last lecture: Basic algorithms for text classification Naive Bayes classifier

676 views • 51 slides

Business Systems Intelligence: 5. Classification 2

606 views • 49 slides

Speaker Verification via Kernel Methods

Speaker Verification via Kernel Methods. Speaker : Yi-Hsiang Chao Advisor : Hsin-Min Wang. OUTLINE. Current Methods for Speaker Verification Proposed Methods for Speaker Verification Kernel Methods for Speaker Verification Experiments Conclusions. What is speaker verification ?.

682 views • 40 slides

Generic object detection with deformable part-based models

Generic object detection with deformable part-based models. Many slides based on P. Felzenszwalb. Challenge: Generic object detection. Histograms of oriented gradients (HOG). Partition image into blocks at multiple scales and compute histogram of gradient orientations in each block.

561 views • 31 slides

General object detection with deformable part-based models

General object detection with deformable part-based models. Many slides based on P. Felzenszwalb. Challenge: Generic object detection. Histograms of oriented gradients (HOG). Partition image into blocks at multiple scales and compute histogram of gradient orientations in each block.

607 views • 30 slides

More sliding window detection: Discriminative part-based models

More sliding window detection: Discriminative part-based models. Many slides based on P . Felzenszwalb. Challenge: Generic object detection. Pedestrian detection. Features: Histograms of oriented gradients (HOG)

403 views • 23 slides

Nonlinear Data Discrimination via Generalized Support Vector Machines

Nonlinear Data Discrimination via Generalized Support Vector Machines. David R. Musicant and Olvi L. Mangasarian University of Wisconsin - Madison. www.cs.wisc.edu/~musicant. Outline. The linear support vector machine (SVM) Linear kernel Generalized support vector machine (GSVM)

714 views • 22 slides

365 views • 22 slides