Computer Vision Toolkit

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Arrange that your organization as an applied scientist for the reinforcement learning team, you have the chance to help develop cutting edge robotic technology by combining reinforcement learning with Computer Vision, localization, and navigation.

More Uses of the Computer Vision Toolkit:

  • Formulate, implement and evaluate Computer Vision or Deep Learning based volumetric data segmentation, and surface reconstruction algorithms.

  • Govern: conduct applied Research and Development in Machine Learning, Deep Learning, Computer Vision and Natural Language Processing.

  • Pilot: design and develop scalable solutions that leverage Machine Learning and Deep Learning models to meet enterprise requirements.

  • Be accountable for creating visualizations of complex data sets and results for ease of understanding by business partners.

  • Write clean readable code, debug complex problems that span systems, prioritize ruthlessly and get things done with a high level of efficiency.

  • Establish: design, build and extract large and complex data sets while thinking strategically about uses of data and how data use interacts with data design.

  • Engage, collect, and label diverse data sources to improve and enrich your Deep Learning based solution.

  • Perform Statistical Modeling, data extraction, analysis, construct, evaluate, and tune Neural Networks.

  • Coordinate with Application Development teams to integrate developed models with existing applications.

  • Construct sophisticated Financial Modeling and keep track of comparable public/private organization data.

  • Direct: design and implement custom Computer Vision algorithms and architectures for commercial product recognition.

  • Contribute to research projects that develop a variety of algorithms and systems in Computer Vision and Machine Learning.

  • Establish: Research and Development of 2D and 3D image analysis algorithms using Image Processing, Computer Vision, and Machine Learning technologies.

  • Establish: deep understand of Deep Learning algorithms and workflows, in particular working with large scale visual data.

  • Manage work with other researchers, engineers, Product Managers, and business partners to rapidly prototype algorithms for Proof of Concept demonstrations.

  • Supervise: design and implement real time estimation, mapping, tracking, classification, and detection algorithms.

  • Ensure you supervise; lead design and implementation of statistical Data Quality procedures for existing and new data sources.

  • Govern: design, develop, test and deploy advanced inference engine techniques and algorithms to enable quick deployment of AI models.

  • Become the expert in Computer Vision and Machine Learning domains as SLAM, 3D reconstruction, object recognition and classification.

  • Oversee: development of robotics vision algorithms, Software Architecture, and Computer Vision software for embedded Software Applications.

  • Utilize Computer Vision techniques to extract features and build Machine Learning applications by training on large datasets.

  • Develop real time, embedded C++ software to decode, interpret, and assemble the raw neural network outputs into a form consumable by the planning and control stack.

  • Pilot: work hand in hand with the Key Stakeholders and developers across your organization using Computer Vision components.

  • Collaborate with robotics and automation specialists, mechanical and Quality Engineers to apply Machine Learning to industrial problems and situations.

  • Establish: design and build Computer Vision solutions for object detection and tracking, scene segmentation, scene understanding, and depth estimation.

  • Control: implement advanced Computer Vision algorithms start with a Proof of Concept, fine tune and optimize as the project evolves.

  • Collaborate with team members on developing Computer Vision systems starting from prototype to production.

  • Develop strategies for technical and Product Development in conjunction with external broadcast and coaching partners.

  • Develop and test software components that implement your analysis methods for integration into production systems.


Save time,, empower your teams and effectively upgrade your processes with access to this practical Computer Vision Toolkit and guide. Address common challenges with best-practice templates, step-by-step Work Plans and maturity diagnostics for any Computer Vision related project.

Download the Toolkit and in Three Steps you will be guided from idea to implementation results.

The Toolkit contains the following practical and powerful enablers with new and updated Computer Vision specific requirements:

STEP 1: Get your bearings

Start with...

  • The latest quick edition of the Computer Vision Self Assessment book in PDF containing 49 requirements to perform a quickscan, get an overview and share with stakeholders.

Organized in a Data Driven improvement cycle RDMAICS (Recognize, Define, Measure, Analyze, Improve, Control and Sustain), check the…

  • Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation

Then find your goals...

STEP 2: Set concrete goals, tasks, dates and numbers you can track

Featuring 999 new and updated case-based questions, organized into seven core areas of Process Design, this Self-Assessment will help you identify areas in which Computer Vision improvements can be made.

Examples; 10 of the 999 standard requirements:

  1. How will measures be used to manage and adapt?

  2. What are the minority interests and what amount of minority interests can be recognized?

  3. If your company went out of business tomorrow, would anyone who doesn't get a paycheck here care?

  4. Do you have past Computer Vision successes?

  5. What Computer Vision requirements should be gathered?

  6. Whom do you really need or want to serve?

  7. Where do you need Computer Vision improvement?

  8. Who will be using the results of the measurement activities?

  9. If you weren't already in this business, would you enter it today? And if not, what are you going to do about it?

  10. What is your formula for success in Computer Vision?

Complete the self assessment, on your own or with a team in a workshop setting. Use the workbook together with the self assessment requirements spreadsheet:

  • The workbook is the latest in-depth complete edition of the Computer Vision book in PDF containing 994 requirements, which criteria correspond to the criteria in...

Your Computer Vision self-assessment dashboard which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next:

  • The Self-Assessment Excel Dashboard; with the Computer Vision Self-Assessment and Scorecard you will develop a clear picture of which Computer Vision areas need attention, which requirements you should focus on and who will be responsible for them:

    • Shows your organization instant insight in areas for improvement: Auto generates reports, radar chart for maturity assessment, insights per process and participant and bespoke, ready to use, RACI Matrix
    • Gives you a professional Dashboard to guide and perform a thorough Computer Vision Self-Assessment
    • Is secure: Ensures offline Data Protection of your Self-Assessment results
    • Dynamically prioritized projects-ready RACI Matrix shows your organization exactly what to do next:


STEP 3: Implement, Track, follow up and revise strategy

The outcomes of STEP 2, the self assessment, are the inputs for STEP 3; Start and manage Computer Vision projects with the 62 implementation resources:

  • 62 step-by-step Computer Vision Project Management Form Templates covering over 1500 Computer Vision project requirements and success criteria:

Examples; 10 of the check box criteria:

  1. Cost Management Plan: Eac -estimate at completion, what is the total job expected to cost?

  2. Activity Cost Estimates: In which phase of the Acquisition Process cycle does source qualifications reside?

  3. Project Scope Statement: Will all Computer Vision project issues be unconditionally tracked through the Issue Resolution process?

  4. Closing Process Group: Did the Computer Vision project team have enough people to execute the Computer Vision project plan?

  5. Source Selection Criteria: What are the guidelines regarding award without considerations?

  6. Scope Management Plan: Are Corrective Actions taken when actual results are substantially different from detailed Computer Vision project plan (variances)?

  7. Initiating Process Group: During which stage of Risk planning are risks prioritized based on probability and impact?

  8. Cost Management Plan: Is your organization certified as a supplier, wholesaler, regular dealer, or manufacturer of corresponding products/supplies?

  9. Procurement Audit: Was a formal review of tenders received undertaken?

  10. Activity Cost Estimates: What procedures are put in place regarding bidding and cost comparisons, if any?

Step-by-step and complete Computer Vision Project Management Forms and Templates including check box criteria and templates.

1.0 Initiating Process Group:

2.0 Planning Process Group:

3.0 Executing Process Group:

  • 3.1 Team Member Status Report
  • 3.2 Change Request
  • 3.3 Change Log
  • 3.4 Decision Log
  • 3.5 Quality Audit
  • 3.6 Team Directory
  • 3.7 Team Operating Agreement
  • 3.8 Team Performance Assessment
  • 3.9 Team Member Performance Assessment
  • 3.10 Issue Log

4.0 Monitoring and Controlling Process Group:

  • 4.1 Computer Vision project Performance Report
  • 4.2 Variance Analysis
  • 4.3 Earned Value Status
  • 4.4 Risk Audit
  • 4.5 Contractor Status Report
  • 4.6 Formal Acceptance

5.0 Closing Process Group:

  • 5.1 Procurement Audit
  • 5.2 Contract Close-Out
  • 5.3 Computer Vision project or Phase Close-Out
  • 5.4 Lessons Learned



With this Three Step process you will have all the tools you need for any Computer Vision project with this in-depth Computer Vision Toolkit.

In using the Toolkit you will be better able to:

  • Diagnose Computer Vision projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices
  • Implement evidence-based best practice strategies aligned with overall goals
  • Integrate recent advances in Computer Vision and put Process Design strategies into practice according to best practice guidelines

Defining, designing, creating, and implementing a process to solve a business challenge or meet a business objective is the most valuable role; In EVERY company, organization and department.

Unless you are talking a one-time, single-use project within a business, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?'

This Toolkit empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Computer Vision investments work better.

This Computer Vision All-Inclusive Toolkit enables You to be that person.


Includes lifetime updates

Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.