Learning and detection of object landmarks in canonical object space Joni-Kristian Kamarainen∗ , Jarmo Ilonen Machine Vision and Pattern Recognition Laboratory ∗ Computational Vision Group, Kouvola Lappeenranta Unive

Source URL: personal.lut.fi

R-CNN: Region-based CNN A framework for object detection with ConvNets aeroplane? no. .. .

Source URL: www.image-net.org

Object Detection Using Multibeam Echosounder Temporal Imagery Lt(N) Mike B. Brissette1, Dr John E. Hughes Clarke2 and Doug Cartwright3 1 Acoustic Data Analysis Centre Pacific, P.O. BoxSTN Forces, Victoria, British

Source URL: www.omg.unb.ca

Improving Object Detection with Deep Convolutional Networks via Bayesian Optimization and Structured Prediction Yuting Zhang*† , Kihyuk Sohn† , Ruben Villegas† , Gang Pan* , Honglak Lee† * Department of Computer

Source URL: web.eecs.umich.edu

Multivac Vision System (MVS): Visual Object Detection and Quality Inspection MVS

Source URL: www.multivac.dk

Biologically Inspired Model for Crater Detection Yang Mu, Wei Ding, Dacheng Tao, and T.F. Stepinski Abstract—Crater detection from panchromatic images has its unique challenges when comparing to the traditional object

Source URL: www.cs.umb.edu

Chained Boosting Christian R. Shelton University of California Riverside CA 92521

Source URL: www.cs.ucr.edu

• Learning
• AdaBoost
• Margin classifier
• Statistical classification
• Viola–Jones object detection framework
• LPBoost
• Statistics
• Artificial intelligence
• Ensemble learning

Sergio Guadarrama Computer Vision SWE Nest / Google http://www.eecs.berkeley.edu/~sguada

Source URL: www.eecs.berkeley.edu

• Object detection
• International Conference on Computer Vision
• Science
• Artificial intelligence
• Activity recognition
• Cognition

accepted at ICRAAffordance Detection of Tool Parts from Geometric Features Austin Myers, Ching L. Teo, Cornelia Ferm¨uller, and Yiannis Aloimonos Abstract— As robots begin to collaborate with humans in

Source URL: www.poeticon.eu

• Affordance
• Bias
• Motor control
• Usability
• Psychology
• Artificial intelligence
• James J. Gibson
• Object recognition
• RGB color model
• Computer vision
• Vision
• Human–computer interaction

Progressive Visual Object Detection with Positive Training Examples Only Ekaterina Riabchenko1 , Ke Chen2 , and Joni-Kristian K¨am¨ar¨ainen2 1 Department of Mathematics and Physics, Lappeenranta University of Technol

Source URL: vision.cs.tut.fi

• Statistics
• Probability and statistics
• Generative model
• Discriminative model
• Constellation model
• Generative
• Pattern recognition
• Histogram of oriented gradients
• Object recognition
• Machine learning
• Artificial intelligence
• Computer vision