Publications by Karim Ali | EPFL Graph Search

Learning Context Cues for Synapse Segmentation

Pascal Fua, Graham Knott, Karim Ali, Carlos Joaquin Becker

We present a new approach for the automated segmentation of synapses in image stacks acquired by Electron Microscopy (EM) that relies on image features specifically designed to take spatial context into account. These features are used to train a classifie ...

Institute of Electrical and Electronics Engineers2013

Data-Driven Visual Tracking in Retinal Microsurgery

Pascal Fua, Raphael Sznitman, Karim Ali

In the context of retinal microsurgery, visual tracking of instruments is a key component of robotics assistance. The difficulty of the task and major reason why most existing strategies fail on {\it in-vivo} image sequences lies in the fact that complex a ...

2012

Learning to Detect Objects with Minimal Supervision

Karim Ali

Many classes of objects can now be successfully detected with statistical machine learning techniques. Faces, cars and pedestrians, have all been detected with low error rates by learning their appearance in a highly generic manner from extensive training ...

EPFL2012

A Real-Time Deformable Detector

David Hasler, Pascal Fua, François Fleuret, Karim Ali

We propose a new learning strategy for object detection. The proposed scheme forgoes the need to train a collection of detectors dedicated to homogeneous families of poses, and instead learns a single classifier that has the inherent ability to deform base ...

Institute of Electrical and Electronics Engineers2012

Learning Context Cues for Synapse Segmentation in EM Volumes

Pascal Fua, Graham Knott, Karim Ali, Carlos Joaquin Becker

We present a new approach for the automated segmentation of excitatory synapses in image stacks acquired by electron microscopy. We rely on a large set of image features specifically designed to take spatial context into account and train a classifier that ...

2012

FlowBoost - Appearance Learning from Sparsely Annotated Video

David Hasler, François Fleuret, Karim Ali

We propose a new learning method which exploits temporal consistency to successfully learn a complex appearance model from a sparsely labeled training video. Our approach consists in iteratively improving an appearance based model built with a Boosting pro ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011

Joint Pose Estimator and Feature Learning for Object Detection

David Hasler, Pascal Fua, François Fleuret, Karim Ali

A new learning strategy for object detection is presented. The proposed scheme forgoes the need to train a collection of detectors dedicated to homogeneous families of poses, and instead learns a single classifier that has the inherent ability to deform ba ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2009