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Heiko Hoffmann

from Simi Valley, CA
Age ~48

Heiko Hoffmann Phones & Addresses

  • 383 Sycamore Grove St, Simi Valley, CA 93065 (213) 804-1642
  • 485 Ellis St, Pasadena, CA 91105 (626) 529-5609
  • Los Angeles, CA
  • Ventura, CA

Resumes

Resumes

Heiko Hoffmann Photo 1

Manager Of Autonomous Intelligence Department

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Location:
Pasadena, CA
Industry:
Research
Work:
Hrl Laboratories, Llc
Manager of Autonomous Intelligence Department

University of Southern California Jan 2007 - Dec 2009
Postdoctorial Researcher

Annie Wang Publications Jan 2007 - Dec 2009
Founder and Owner

The University of Edinburgh Feb 2006 - Dec 2006
Postdoctoral Researcher

The University of Western Australia Feb 2001 - Aug 2001
Visiting Scholar
Education:
Max Planck Institute For Human Cognitive and Brain Sciences 2001 - 2005
Doctorates, Doctor of Philosophy, Robotics
Heidelberg University 1997 - 2001
Master of Science, Masters, Physics
Technische Universität Darmstadt 1996 - 1997
Skills:
Machine Learning
Robotics
Physics
Matlab
Algorithms
Pattern Recognition
Simulations
Science
Project Management
Computer Vision
Latex
Proposal Writing
Image Processing
Sensors
Data Mining
Leadership
C++
Computational Neuroscience
Mathematical Modeling
Drawing
Presentations
Strategic Planning
Ios Development
Php
Objective C
Java
Android Development
Graphic Design
Data Science
Javascript
Python
Landscape Design
Irrigation System Installation
Interests:
Biomedical Engineering
Human Motor Control
Robotics
General Science
Web Design
See 1
Consulting
Marketing
See Less
Machine Learning
Meeting People
Founding A Company
Data Science
Languages:
German
English
Mandarin
French
Heiko Hoffmann Photo 2

Heiko Hoffmann

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Heiko Hoffmann Photo 3

Heiko Hoffmann

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Business Records

Name / Title
Company / Classification
Phones & Addresses
Heiko Hoffmann
Principal
Annie Wang Publications
Misc Publishing
2082 Heather St, Simi Valley, CA 93065

Publications

Us Patents

Method And System For Error Correction In Automated Wire Contact Insertion Within A Connector

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US Patent:
20210399470, Dec 23, 2021
Filed:
Jun 19, 2020
Appl. No.:
16/906536
Inventors:
- Chicago IL, US
Heiko HOFFMANN - Malibu CA, US
International Classification:
H01R 13/641
B25J 19/02
B25J 9/16
G06T 7/70
Abstract:
A method, system and computer program product are provided for correction of automated insertion of a wire contact into a target hole of a connector. Methods include controlling a robot having an end-effector to: align the wire contact with the target hole of the connector; advance the wire contact toward and into the target hole of the connector; cease insertion in response to a force between the wire contact and the connector exceeding a predefined value; determining a depth of insertion; in response to the depth of insertion being above a predefined depth, perform a pull test on the inserted wire contact; in response to the depth of insertion being below a predetermined depth, identify an error condition using visual feedback; determine a number of corrective operations performed and perform error correction if the number is below a predefined number, while withdrawing the wire contact otherwise.

Learning Actions With Few Labels In The Embedded Space

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US Patent:
20210089762, Mar 25, 2021
Filed:
Jul 16, 2020
Appl. No.:
16/931420
Inventors:
- Malibu CA, US
Heiko Hoffmann - Simi Valley CA, US
Soheil Kolouri - Agoura Hills CA, US
International Classification:
G06K 9/00
G06K 9/62
G06T 7/70
Abstract:
Described is a system for learning actions for image-based action recognition in an autonomous vehicle. The system separates a set of labeled action image data from a source domain into components. The components are mapped onto a set of action patterns, thereby creating a dictionary of action patterns. For each action in the set of labeled action data, a mapping is learned from the action pattern representing the action onto a class label for the action. The system then maps a set of new unlabeled target action image data onto a shared embedding feature space in which action patterns can be discriminated. For each target action in the set of new unlabeled target action image data, a class label for the target action is identified. Based on the identified class label, the autonomous vehicle is caused to perform a vehicle maneuver corresponding to the identified class label.

Method And System For Alignment Of Wire Contact With Wire Contact Insertion Holes Of A Connector

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US Patent:
20210044069, Feb 11, 2021
Filed:
Aug 9, 2019
Appl. No.:
16/536622
Inventors:
- Chicago IL, US
Heiko HOFFMANN - Malibu CA, US
International Classification:
H01R 43/20
G06T 7/73
G06T 7/13
G06T 7/00
B25J 9/16
Abstract:
A method, system and computer program product are provided for aligning wire contacts with wire contact insertion holes of a connector to facilitate the automated insertion of the wire ends of a wire bundle assembly into the wire contact insertion holes of a connector. Methods may include: obtaining captured images from at least two image capture devices attached to an end-effector of a robot of a wire gripper of the end-effector; detecting, within at least one image from each of the at least two image capture devices, a wire contact; detecting, within at least one image from each of the at least two image capture devices, one or more insertion holes of the connector; identifying corrective movement for the robot end-effector that aligns a target hole of the one or more insertion holes of the connector with the wire connector; and causing the robot to move the end-effector according to the identified corrective movement.

Method And System For Alignment And Insertion Of Wire Contact With Wire Contact Insertion Holes Of A Connector

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US Patent:
20210044070, Feb 11, 2021
Filed:
Aug 9, 2019
Appl. No.:
16/536598
Inventors:
- Chicago IL, US
Richard J. PATRICK - Irvine CA, US
Heiko HOFFMANN - Malibu CA, US
International Classification:
H01R 43/28
H01R 13/41
H01R 13/52
Abstract:
A method, system and computer program product are provided for aligning and inserting a wire contact within a target hole of a connector to facilitate the automated insertion of the wire ends of a wire bundle assembly into the wire contact insertion holes of a connector. Methods may include: obtaining captured images, from at least two image capture devices attached to an end-effector of a robot, of a wire gripper of the end-effector; causing the robot to advance the end-effector to move the wire contact within a predetermined distance of the connector; causing the robot to advance the end-effector to move the wire contact toward the connector a predetermined additional amount more; and identifying, based on movement of the wire contact the predetermined additional amount more, if alignment is correct from force feedback at the wire gripper.

Action Classification Using Deep Embedded Clustering

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US Patent:
20210012100, Jan 14, 2021
Filed:
May 13, 2020
Appl. No.:
15/931258
Inventors:
- Malibu CA, US
Heiko Hoffmann - Simi Valley CA, US
International Classification:
G06K 9/00
G06K 9/62
G06N 3/04
G05D 1/00
Abstract:
Described is a system for action recognition through application of deep embedded clustering. For each image frame of an input video, the system computes skeletal joint-based pose features representing an action of a human in the image frame. Non-linear mapping of the pose features into an embedded action space is performed. Temporal classification of the action is performed and a set of categorical gesture-based labels is obtained. The set of categorical gesture-based labels is used to control movement of a machine.

System And Method For Detecting Backdoor Attacks In Convolutional Neural Networks

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US Patent:
20200410098, Dec 31, 2020
Filed:
Apr 21, 2020
Appl. No.:
16/854875
Inventors:
- Malibu CA, US
Heiko Hoffmann - Simi Valley CA, US
International Classification:
G06F 21/56
G06N 3/04
G06K 9/62
G06F 8/41
Abstract:
Described is a system for detecting backdoor attacks in deep convolutional neural networks (CNNs). The system compiles specifications of a pretrained CNN into an executable model, resulting in a compiled model. A set of Universal Litmus Patterns (ULPs) are fed through the compiled model, resulting in a set of model outputs. The set of model outputs are classified and used to determine presence of a backdoor attack in the pretrained CNN. The system performs a response based on the presence of the backdoor attack.

Three-Dimensional Point Data Alignment With Pre-Alignment

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US Patent:
20200211293, Jul 2, 2020
Filed:
Jan 2, 2019
Appl. No.:
16/238002
Inventors:
- Chicago IL, US
Heiko Hoffmann - Simi Valley CA, US
International Classification:
G06T 19/20
G06T 17/00
G01S 17/42
G01S 17/89
G05D 1/08
Abstract:
An apparatus to generate a model of a surface of an object includes a data set pre-aligner configured to receive multiple sets of surface data that correspond to respective portions of a surface of an object and that include three-dimensional (3D) points. The data set pre-aligner is also configured to perform a pre-alignment of overlapping sets to generate pre-aligned sets, including performing a rotation operation on a second set of the surface data, relative to a first set of the surface data that overlaps the second set, to apply a rotation amount that is selected from among multiple discrete rotation amounts and based on a similarity metric. The apparatus includes a data set aligner configured to perform an iterative alignment of the pre-aligned sets to generate aligned sets. The apparatus also includes a 3D model generator configured to combine the aligned sets to generate a 3D model of the object.

Method And System For Detecting Change Of Context In Video Streams

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US Patent:
20190370598, Dec 5, 2019
Filed:
May 17, 2019
Appl. No.:
16/415942
Inventors:
- Malibu CA, US
Nigel D. Stepp - Santa Monica CA, US
Soheil Kolouri - Agoura Hills CA, US
Heiko Hoffmann - Simi Valley CA, US
International Classification:
G06K 9/46
G06N 3/08
G06K 9/62
Abstract:
Described is a system for detecting change of context in a video stream on an autonomous platform. The system extracts salient patches from image frames in the video stream. Each salient patch is translated to a concept vector. A recurrent neural network is enervated with the concept vector, resulting in activations of the recurrent neural network. The activations are classified, and the classified activations are mapped onto context classes. A change in context class is detected in the image frames, and the system causes the autonomous platform to perform an automatic operation to adapt to the change of context class.
Heiko Hoffmann from Simi Valley, CA, age ~48 Get Report