This document describes research on bio-inspired active vision systems. It discusses how biological vision differs from traditional computer vision in being active rather than passive. The researchers are developing active vision systems using an evolutionary robotics approach, involving neural networks and genetic algorithms. Previous related work is described, including obstacle avoidance by Mars rovers and koala robots. The document outlines plans to design an active vision system to recognize objects using a dataset of images under different conditions, and accelerate it with GPUs. Results showed the system learned to correctly classify objects over generations.
This presentation shows the impact of GPU computing on cognitive robotics by showing a series of novel experiments in the area of action and language acquisition in humanoid robots and computer vision. Cognitive robotics is concerned with endowing robots with high-level cognitive capabilities to enable the achievement of complex goals in complex environments. Reaching the ultimate goal of developing cognitive robots will require tremendous amount of computational power, which was until recently provided mostly by standard CPU processors. However, CPU cores are optimised for serial code execution at the expense of parallel execution, which renders them relatively inefficient when it comes to high-performance computing applications. The ever-increasing market demand for high-performance, real-time 3D graphics has evolved the GPU into highly parallel, multithreaded, many-core processor extraordinary computational power and very high memory bandwidth. These vast computational resources of modern GPUs can now be used by the most of the cognitive robotics models as they tend to be inherently parallel. Various interesting and insightful cognitive models were developed and addressed important scientific questions concerning action-language acquisition and computer vision. While they have provided us with important scientific insights, their complexity and application has not improved much over the last years. The experimental tasks as well as the scale of these models are often minimised to avoid excessive training times that grow exponentially with the number of neurons and the training data. However, this impedes further progress and development of complex neurocontrollers that would be able to take the cognitive robotics research a step closer to reaching the ultimate goal of creating intelligent machines. This presentation shows several cases where the application of the GPU computing on cognitive robotics algorithms resulted in the development of large-scale neurocontrollers of previously unseen complexity, which enabled conducting the novel experiments described herein.
The 2010 annual report, covering the activity of the whole Institute, is now available in two formats: in the print version and in the on-line version that can be consulted online. It is an opportunity to look back over an eventful year and to share this document which is both important and at the same time enjoyable to read.
Human motion is fundamental to understanding behaviour. In spite of advancement on single image 3 Dimensional pose and estimation of shapes, current video-based state of the art methods unsuccessful to produce precise and motion of natural sequences due to inefficiency of ground-truth 3 Dimensional motion data for training. Recognition of Human action for programmed video surveillance applications is an interesting but forbidding task especially if the videos are captured in an unpleasant lighting environment. It is a Spatial-temporal feature-based correlation filter, for concurrent observation and identification of numerous human actions in a little-light environment. Estimated the presentation of a proposed filter with immense experimentation on night-time action datasets. Tentative results demonstrate the potency of the merging schemes for vigorous action recognition in a significantly low light environment.
Toward Tractable AGI: Challenges for System Identification in Neural CircuitryRandal Koene
This is the presentation I gave at AGI-12 (also called the Winter Intelligence 2012 conferece) in Oxford, UK, on Dec.11, 2012. There is an AGI-12 proceedings paper that accompanies this talk. I will make that available on my publications page at http://randalkoene.com and I will put both together on the http://carboncopies.org page about this event. The video (recorded by Adam Ford) should also appear soon.
Abstract. Feasible and practical routes to Artificial General Intelligence involve short-cuts tailored to environments and challenges. A prime example of a system with built-in short-cuts is the human brain. Deriving from the brain the functioning system that implements intelligence and generality at the level of neurophysiology is interesting for many reasons, but also poses a set of specific challenges. Representations and models demand that we pick a constrained set of signals and behaviors of interest. The systematic and iterative process of model building involves what is known as System Identification, which is made feasible by decomposing the overall problem into a collection of smaller System Identification problems. There is a roadmap to tackle that includes structural scanning (a way to obtain the “connectome”) as well as new tools for functional recording. We examine the scale of the endeavor, and the many challenges that remain, as we consider specific approaches to System Identification in neural circuitry.
This presentation shows the impact of GPU computing on cognitive robotics by showing a series of novel experiments in the area of action and language acquisition in humanoid robots and computer vision. Cognitive robotics is concerned with endowing robots with high-level cognitive capabilities to enable the achievement of complex goals in complex environments. Reaching the ultimate goal of developing cognitive robots will require tremendous amount of computational power, which was until recently provided mostly by standard CPU processors. However, CPU cores are optimised for serial code execution at the expense of parallel execution, which renders them relatively inefficient when it comes to high-performance computing applications. The ever-increasing market demand for high-performance, real-time 3D graphics has evolved the GPU into highly parallel, multithreaded, many-core processor extraordinary computational power and very high memory bandwidth. These vast computational resources of modern GPUs can now be used by the most of the cognitive robotics models as they tend to be inherently parallel. Various interesting and insightful cognitive models were developed and addressed important scientific questions concerning action-language acquisition and computer vision. While they have provided us with important scientific insights, their complexity and application has not improved much over the last years. The experimental tasks as well as the scale of these models are often minimised to avoid excessive training times that grow exponentially with the number of neurons and the training data. However, this impedes further progress and development of complex neurocontrollers that would be able to take the cognitive robotics research a step closer to reaching the ultimate goal of creating intelligent machines. This presentation shows several cases where the application of the GPU computing on cognitive robotics algorithms resulted in the development of large-scale neurocontrollers of previously unseen complexity, which enabled conducting the novel experiments described herein.
The 2010 annual report, covering the activity of the whole Institute, is now available in two formats: in the print version and in the on-line version that can be consulted online. It is an opportunity to look back over an eventful year and to share this document which is both important and at the same time enjoyable to read.
Human motion is fundamental to understanding behaviour. In spite of advancement on single image 3 Dimensional pose and estimation of shapes, current video-based state of the art methods unsuccessful to produce precise and motion of natural sequences due to inefficiency of ground-truth 3 Dimensional motion data for training. Recognition of Human action for programmed video surveillance applications is an interesting but forbidding task especially if the videos are captured in an unpleasant lighting environment. It is a Spatial-temporal feature-based correlation filter, for concurrent observation and identification of numerous human actions in a little-light environment. Estimated the presentation of a proposed filter with immense experimentation on night-time action datasets. Tentative results demonstrate the potency of the merging schemes for vigorous action recognition in a significantly low light environment.
Toward Tractable AGI: Challenges for System Identification in Neural CircuitryRandal Koene
This is the presentation I gave at AGI-12 (also called the Winter Intelligence 2012 conferece) in Oxford, UK, on Dec.11, 2012. There is an AGI-12 proceedings paper that accompanies this talk. I will make that available on my publications page at http://randalkoene.com and I will put both together on the http://carboncopies.org page about this event. The video (recorded by Adam Ford) should also appear soon.
Abstract. Feasible and practical routes to Artificial General Intelligence involve short-cuts tailored to environments and challenges. A prime example of a system with built-in short-cuts is the human brain. Deriving from the brain the functioning system that implements intelligence and generality at the level of neurophysiology is interesting for many reasons, but also poses a set of specific challenges. Representations and models demand that we pick a constrained set of signals and behaviors of interest. The systematic and iterative process of model building involves what is known as System Identification, which is made feasible by decomposing the overall problem into a collection of smaller System Identification problems. There is a roadmap to tackle that includes structural scanning (a way to obtain the “connectome”) as well as new tools for functional recording. We examine the scale of the endeavor, and the many challenges that remain, as we consider specific approaches to System Identification in neural circuitry.
Aquila: An Open-Source GPU-Accelerated Toolkit for Cognitive and Neuro-Roboti...Martin Peniak
These slide are from the NVIDIA GTC Express Webminar presented by Martin Peniak and Anthony Morse. There should be an audio/video version available at NVIDIA GTC site below.
http://www.gputechconf.com/object/gtc-express-webinar.html
The presentation focuses on the cognitive robotics research, GPUs and Aquila, an open-source toolkit providing many different tools and biologically-inspired models, useful for cognitive and developmental robotics research. Aquila addresses the need for high-performance robot control, which is typically confounded by processing power limitations that are inherent in the standard CPU architectures.
Presentation held by Sieow Yeek Tan, Dickson Lukose at the Agricultural Ontology Service (AOS) Workshop 2012 in Kutching, Sarawak, Malaysia from September 3 - 4, 2012
Artificial Intelligence is being supplanted by "Artificial Brain," i.e. neuromorphic technologies. Yet there still a whopping gap that neuromorphic systems need to close before they will become a match for successful AI applications.
Soft computing is an umbrella term used to describe types of algorithms that produce approximate solutions to unsolvable high-level problems in computer science.
What is Aquila Software Architecture for Cognitive Robotics?Martin Peniak
Aquila 2.0, an open-source cross-platform software architecture for cognitive robotics that makes use of independent heterogeneous CPU-GPU modules with loosely coupled dynamically generated graphical user interfaces.
Aquila: An Open-Source GPU-Accelerated Toolkit for Cognitive and Neuro-Roboti...Martin Peniak
These slide are from the NVIDIA GTC Express Webminar presented by Martin Peniak and Anthony Morse. There should be an audio/video version available at NVIDIA GTC site below.
http://www.gputechconf.com/object/gtc-express-webinar.html
The presentation focuses on the cognitive robotics research, GPUs and Aquila, an open-source toolkit providing many different tools and biologically-inspired models, useful for cognitive and developmental robotics research. Aquila addresses the need for high-performance robot control, which is typically confounded by processing power limitations that are inherent in the standard CPU architectures.
Presentation held by Sieow Yeek Tan, Dickson Lukose at the Agricultural Ontology Service (AOS) Workshop 2012 in Kutching, Sarawak, Malaysia from September 3 - 4, 2012
Artificial Intelligence is being supplanted by "Artificial Brain," i.e. neuromorphic technologies. Yet there still a whopping gap that neuromorphic systems need to close before they will become a match for successful AI applications.
Soft computing is an umbrella term used to describe types of algorithms that produce approximate solutions to unsolvable high-level problems in computer science.
What is Aquila Software Architecture for Cognitive Robotics?Martin Peniak
Aquila 2.0, an open-source cross-platform software architecture for cognitive robotics that makes use of independent heterogeneous CPU-GPU modules with loosely coupled dynamically generated graphical user interfaces.
Fluoridation, the scientific fraud of a centuryMartin Peniak
An overwhelming number of independent scientific research has shown that fluoride is a neurotoxin causing lower IQs[1], cancer[2][3], changing bone structure and strength[4-11], birth defects and prenatal deaths[12], acute adverse reactions[13][14], skeletal fluorosis[15][16], increased lead levels in blood[17], osteoarthritis[18], repetitive stress injury[19], permanent disfigurement of teeth in children[20], inhibiting of key enzymes and negatively affecting neural system[21], suppressed thyroid function[22-27], acute poisoning and impairment of the immune system[14].
Introduction to humanoid robot iCub, YARP and simulatorMartin Peniak
This is a very basic introduction to humanoid robotic platform iCub, YARP (Yet Another Robotic Platform) - software that is used to facilitate communication with the robot and also iCub simulator that is a tool that we use first to develop our system before we deploy it on the real physical robot.
Co-evolving controller and sensing abilities in a simulated Mars Rover explorerMartin Peniak
M. Peniak, D.Marocco, A. Cangelosi (2009). Co-evolving controller and sensing abilities in a simulated Mars Rover explorer. IEEE Congress on Evolutionary Computation (CEC) 2009. Trondheim, Norway, 18th-21nd May
Vedecká evidencia poukazujúca na spojenie hmoty a vedomiaMartin Peniak
Vedecká evidencia poukazujúca na spojenie hmoty a vedomia. Túto evidenciu som prezentoval 25 augusta 2009 v K KLUBE, Detva, Slovenko.
Začína stručným prehľadom vedeckého pokroku za posledných pár storočí, prechádza cez 10 vedeckých experimentov, ktoré jasne poukazujú na toto spojenie. Ku koncu pojednávam o pohľade na realitu ako hologram čo sa zdá byť najlepšie vysvetlujúci model mozgu, vesmíru a vôbec reality ako takej.
Taktiež táto prezentácia sa opiera o poznaty z biológie, kvantovej mechaniky, astronómie, neurológie a pod.
Jej jediným účelom bolo priniesť najnovšie informácie, ktoré môžno ešte niesú také bežné na Slovenku kvôli jazykovej bariére. Záver je zameraný na bežného človeka a aku mu tieto poznatky môžu pomôcť rozšíriť pohľad na realitu na jeho silu s ňou vedome manipulovať silou mysle a emócií.
Nech sú všetky bytosti šťastné :)
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
2. Outline
Introduction
Classical vision vs. active vision
Show few examples, e.g. template matching, face detection etc.
Pros&Cons
Explain what is active perception (use current + davides slides)
Active Vision – many possibilities but we like GA+NN, why?
Based on neural network and genetic algorithm
What is neural network?
What is genetic algorithm?
Pros&Cons
Little computation required due to neural network architecture, fast
No external representation needed thanks to GA evolving nn weights
Generality, invariance, and application in multiple domains
Cons: need more research, so far applied in limited domains
Previous research by Floreano, Davide, me (ESA)
Show videos and pictures
Describe work done at NVIDIA
Future work: AXA grant
2
5. Traditional Computer Vision
“Teaching a computer to classify objects has proved much harder than was originally anticipated”
Thomas Serre - Center for Biological and Computational Learning at MIT
Specific template or computational
representation is required to allow object
recognition
Must be flexible enough to account with all
kinds of variations
5
6. Biological Vision
“Researchers have been interested for years in trying to copy biological vision systems,
simply because they are so good” ~ David Hogg - computer vision expert at Leeds University, UK
Highly optimized over millions of years of
evolution, developing complex neural structures
to represent and process stimuli
Superiority of biological vision systems is only
partially understood
Hardware architecture and the style of
computation in nervous systems are
fundamentally different 6
9. Active Vision
Inspired by the vision systems of natural organisms that have
been evolving for millions of years
In contrast to standard computer vision systems, biological
organisms actively interact with the world in order to make sense
of it
Humans and also other animals do not look at a scene in fixed
steadiness. Instead, they actively explore interesting parts of the
scene by rapid saccadic movements
9
11. Evolutionary Robotics
New technique for the automatic creation of autonomous robots
Inspired by the Darwinian principle of selective reproduction of
the fittest
Views robots as autonomous artificial organisms that develop
their own skills in close interaction with the environment and
without human intervention
Drawing heavily on biology and ethology, it uses the tools of
neural networks, genetic algorithms, dynamic systems, and
biomorphic engineering
11
12. Genetic Algorithms (GAs) are adaptive heuristic search
algorithm premised on the evolutionary ideas of natural
selection and genetic. The basic concept of GAs is
... designed to simulate processes in natural system
necessary for evolution.
Population
(Chromosomes)
...
...
Genetic Evaluation
operators (Fitness)
Artificial neural networks (ANNs) are very powerful brain-inspired Selection
(Mating Pool)
computational models, which have been used in many different
12
areas such as engineering, medicine, finance, and many others.
19. Method
Evolution of the active vision system for real-world object recognition
training the system in a parallel manner on multiple objects viewed from many different angles and under different lighting conditions
Amsterdam Library of Object Images (ALOI)
provides a color image collection of one-thousand small objects
recorded for scientific purposes
systematically varied viewing angle, illumination angle, and illumination color
Active Vision Training
trained on a set of objects from the ALOI library
each genotype is evaluated during multiple trials with different randomly rotated objects and under varying lighting conditions
evolutionary pressure provided by a fitness function that evaluates overall success or failure of the object classification
trained on increasingly larger number of objects
Active Vision Testing
robustness and resiliency of recognition of the dataset
generalization to previously unseen instances of the learned objects
19
20. Experimental Setup
Recurrent Neural Network
Inputs: 8x8 neurons for retina, 2 neurons for proprioception (x,y pos)
No hidden neurons
Outputs: 5 object recognition neurons, 2 neurons to move retina (16px max)
Genetic Algorithm
Generations: 10000
Number of individuals: 100
Number of trials: 36+16 (object rotations + varying lighting conditions)
Mutation probability: 10%
Reproduction: best 20% of individuals create new population
Elitism used (best individual is preserved)
20
21. Experimental Setup
Each individual (neural network) could freely move the retina and
read the input from the source image (128x128) for 20 steps
At each step, neural network controlled the behavior of the
system (retina position) and provide recognition output
The recognition output neuron with the highest activation was
considered the network’s guess about what the object was
Fitness function = number of correct answers / number of total steps
21
22. GPU Accelerating GA and ANN
GPUs were used to accelerate:
Evolutionary process – parallel execution of trials
Neural Network – parallel calculation of neural activities
22
23. Results
Fitness can not reach 1.0 since it takes few time-steps to recognize an object
All objects are correctly classified at the end of the each test
0.9
0.8
0.7
0.6
0.5
fitness
0.4
0.3
0.2
0.1
0
0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000
generations
best fitness average fitness
23