About
Articles by Lovell
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Bringing Together the Best and Brightest in AI: A Comprehensive Approach
Bringing Together the Best and Brightest in AI: A Comprehensive Approach
By Lovell Hodge Ph.D.
Activity
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What a week visiting Manulife Japan's Tokyo office - stunnng view, superb team, and exciting GenAI projects!
What a week visiting Manulife Japan's Tokyo office - stunnng view, superb team, and exciting GenAI projects!
Liked by Lovell Hodge Ph.D.
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Here we are. Thank you to Multichannel News Wonder Women Awards. Congratulations to all my extraordinary sister honorees who have demonstrated…
Here we are. Thank you to Multichannel News Wonder Women Awards. Congratulations to all my extraordinary sister honorees who have demonstrated…
Liked by Lovell Hodge Ph.D.
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I was delighted to sit down with the Genpact team to discuss the transformation of enterprise data into a strategic asset. The multi-part series…
I was delighted to sit down with the Genpact team to discuss the transformation of enterprise data into a strategic asset. The multi-part series…
Shared by Lovell Hodge Ph.D.
Experience & Education
Publications
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Scalability and optimality in a multi-agent sensor planning system
Proceedings World Automation Congress, 2004.
The objective of this research is to investigate the scalability and optimality of an automated system for multiple sensor planning using multiple communicating agents. The problem domain is such that a single sensor system would not provide adequate information for a given sensor task. Due to the inherently complex interdependencies of multi-sensor systems, traditional optimization algorithms for sensor placement are not flexible enough to provide real time scalability and flexibility. This…
The objective of this research is to investigate the scalability and optimality of an automated system for multiple sensor planning using multiple communicating agents. The problem domain is such that a single sensor system would not provide adequate information for a given sensor task. Due to the inherently complex interdependencies of multi-sensor systems, traditional optimization algorithms for sensor placement are not flexible enough to provide real time scalability and flexibility. This research addresses those limitations. Empirical results suggest that polynomial convergence is maintained even as the number of sensors is increased.
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An agent-based approach to multisensor coordination
IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans ( Volume: 33 , Issue: 5 , Sept. 2003 )
This paper presents an automated system for multiple sensor placement based on the coordinated decisions of independent, intelligent agents. The problem domain is such that a single sensor system would not provide adequate information for a given sensor task. Hence, it is necessary to incorporate multiple sensors in order to obtain complete information. The overall goal of the system is to provide the surface coverage necessary to perform feature inspection on one or more target objects in a…
This paper presents an automated system for multiple sensor placement based on the coordinated decisions of independent, intelligent agents. The problem domain is such that a single sensor system would not provide adequate information for a given sensor task. Hence, it is necessary to incorporate multiple sensors in order to obtain complete information. The overall goal of the system is to provide the surface coverage necessary to perform feature inspection on one or more target objects in a cluttered scene. This is accomplished by a group of cooperating intelligent sensors. In this system, the sensors are mobile, the target objects are stationary and each agent controls the position of a sensor and has the ability to communicate with other agents in the environment. By communicating desires and intentions, each agent develops a mental model of the other agents' preferences, which is used to avoid or resolve conflict situations. In this paper we utilize cameras as the sensors. The experimental results illustrate the feasibility of the autonomous deployment of the sensors and that this deployment can occur with sufficient accuracy as to allow the inspection task to be performed.
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A coordination mechanism for model-based multi-sensor planning
Proceedings of the IEEE International Symposium on Intelligent Control
This paper presents a multi-agent system for coordinating the deployment of multiple sensors in a modeled environment. The sensing task is the maximal sensor coverage of one or more targets in a scene and the position of each sensor is controlled by an autonomous agent. The agents rely on negotiation to achieve the level of coordination necessary to accomplish the given sensing task.
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An adaptive training algorithm for an ensemble of networks
IJCNN'01. International Joint Conference on Neural Networks
An ensemble of neural networks offers several advantages over classical single classifier systems when applied to complex pattern classification problems. However, the performance of the ensemble as a unit depends not only on the effective aggregation of the modules decisions, but also on the accuracy of the individual classification decisions of each module. The accuracy at the modular level is a result of the quality of training received by each module. This paper presents an adaptive…
An ensemble of neural networks offers several advantages over classical single classifier systems when applied to complex pattern classification problems. However, the performance of the ensemble as a unit depends not only on the effective aggregation of the modules decisions, but also on the accuracy of the individual classification decisions of each module. The accuracy at the modular level is a result of the quality of training received by each module. This paper presents an adaptive training algorithm that can be used to direct the training of the individual modules so as to improve the classification accuracy and training efficiency of the ensemble.
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Learning decision fusion in cooperative modular neural networks
IJCNN'99. International Joint Conference on Neural Networks
The modular neural network offers several advantages over classical non-modular neural network approaches to complex pattern classification problems. However, the accuracy of the modular approach depends greatly on the accurate fusion of the individual classification decisions. The paper presents a method for improving the overall accuracy of modular neural networks by incorporating an adaptive decision fusion mechanism. The proposed algorithm offers significant improvement over typical modular…
The modular neural network offers several advantages over classical non-modular neural network approaches to complex pattern classification problems. However, the accuracy of the modular approach depends greatly on the accurate fusion of the individual classification decisions. The paper presents a method for improving the overall accuracy of modular neural networks by incorporating an adaptive decision fusion mechanism. The proposed algorithm offers significant improvement over typical modular networks by evolving a more informed decision fusion mechanism that can greatly improve the final classification decision for complex classification tasks.
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An artificial neural network hierarchy for the analysis of cell data
IEEE International Joint Conference on Neural Networks Proceedings
This paper presents an investigation of the use of artificial neural networks in a hierarchical arrangement for the classification of cell image data obtained from smears. The aim is to distinguish between various types of cells and possibly noncellular material based on one or more distinct feature sets obtained from the image data. The extremely divergent characteristics of the cell data makes this a real world classification problem with no easy solution. The paper focuses on the use of…
This paper presents an investigation of the use of artificial neural networks in a hierarchical arrangement for the classification of cell image data obtained from smears. The aim is to distinguish between various types of cells and possibly noncellular material based on one or more distinct feature sets obtained from the image data. The extremely divergent characteristics of the cell data makes this a real world classification problem with no easy solution. The paper focuses on the use of backpropagation and learning vector quantization as the artificial neural network classification algorithms. A methodology for the design of the classification hierarchy is presented and the results of experiments involving cell data from smears are analyzed.
Honors & Awards
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Principles and Practice Award for outstanding contributions
TD Bank
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Best Speaker Award
International Joint Conference on Artificial Intelligence (Washington DC)
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Business Banking Quarterly Award for Outstanding Performance
TD Bank
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Dr. Philip H Byrne Award for Ingenuity
Ryerson University
Organizations
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Association for the Advancement of Artificial Intelligence
Member
More activity by Lovell
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🌟 We are thrilled to announce that Mr. Rajnish Ranjan has joined CyborgIntell as our Head - Data Science! 🌟 👨💻 An alumni of Indian Statistical…
🌟 We are thrilled to announce that Mr. Rajnish Ranjan has joined CyborgIntell as our Head - Data Science! 🌟 👨💻 An alumni of Indian Statistical…
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Absolutely loved immersing myself in the dynamic atmosphere of the Big Data & Analytics Canada summit over the past two days! The passion and…
Absolutely loved immersing myself in the dynamic atmosphere of the Big Data & Analytics Canada summit over the past two days! The passion and…
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What an amazing day. Was great to reconnect with some of my ELCI friends and re-immerse myself in the world of cybersecurity. From fireworks to…
What an amazing day. Was great to reconnect with some of my ELCI friends and re-immerse myself in the world of cybersecurity. From fireworks to…
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I am so happy and grateful to be part such a great team and to be able to provide support to our youth. Being part of their journey, motivates me to…
I am so happy and grateful to be part such a great team and to be able to provide support to our youth. Being part of their journey, motivates me to…
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As I transition from my role as CEO to continue as an ongoing board member and substantial stakeholder, I reflect on my journey at Zafin with immense…
As I transition from my role as CEO to continue as an ongoing board member and substantial stakeholder, I reflect on my journey at Zafin with immense…
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This past week my father retired and left Dubai after 33 years. His journey has been very inspiring from being born in #Somalia, growing up in…
This past week my father retired and left Dubai after 33 years. His journey has been very inspiring from being born in #Somalia, growing up in…
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When considering a summarization solution for your underwriting or claims needs, make sure you are asking the right questions. Friendly is here to…
When considering a summarization solution for your underwriting or claims needs, make sure you are asking the right questions. Friendly is here to…
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Curious about #LargeLanguageModels? Check out this article where Munich Re's Lovell Hodge Ph.D. explores the challenges and considerations when…
Curious about #LargeLanguageModels? Check out this article where Munich Re's Lovell Hodge Ph.D. explores the challenges and considerations when…
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An unforgettable evening at the Quantum Innovation Summit Gala in Dubai! Honored to receive an award amidst the glitz and glamour of this magical…
An unforgettable evening at the Quantum Innovation Summit Gala in Dubai! Honored to receive an award amidst the glitz and glamour of this magical…
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