Resources

On this page I share a variety of resources related to my courses, talks, and research interests. I plan to update it often.
Please contact me with specific requests or suggestions.

Slides and supporting materials for lectures and talks

• Invited talk: “ACR AI-Lab for radiology: an overview”, European Society of Medical Imaging Informatics (EuSoMII) Annual Meeting, Valencia, Spain, October 2019. [slides]
• Oral presentation of the abstract: O. Marques and L. Zaniolo, “Evaluation of the Use of Convolutional Neural Networks with Variable Stride for Skin Lesion Classification”, European Society of Medical Imaging Informatics (EuSoMII) Annual Meeting, Valencia, Spain, October 2019. [slides]
• Oral presentation of the abstract: O. Marques, A. Ishay, A. Elshaikh, W.A. Andrews, A. Bulatovic, and H.M. Do, “Assessing the impact of image quality on brain MRI diagnosis using deep learning”, European Society of Medical Imaging Informatics (EuSoMII) Annual Meeting, Valencia, Spain, October 2019. [slides]
• Invited talk: “Medical image analysis and medical information retrieval, with and without deep learning”, Lister Hill National Center for Biomedical Communications, National Library of Medicine (NLM), National Institutes of Health (NIH), Bethesda, MD, October 2018. [slides]
• Oral presentation of the abstract: J. Burdick, O. Marques, A. Romero Lopez, X. Giro-i-Nieto, and J. Weinthal, “The impact of segmentation on the accuracy and sensitivity of a melanoma classifier based on skin lesion images,” SIIM Annual Meeting, Pittsburgh, PA, June 2017. [slides]
• Invited talk: “Machine Learning and Applications”, Indian Institute of Information Technology and Management, Kerala (IIITM-K), Trivandrum, India, December 2016. [slides]
• Plenary talk: “Inspiring Actions for Successful Engineering Education”, Fourth IEEE International Conference on MOOCs, Innovation and Technology in Education (MITE 2016), Madurai, India, December 2016. [slides]
• Keynote speech: “Visual Information Retrieval: Advances, Challenges and Opportunities”, 4^th International Conference on Advances in Computing, Communications and Informatics (ICACCI) – Kochi, India, August 2015. [slides]
• Invited talk: “Promoting Digital Fluency on Campus”, Teaching with Technology Showcase, Florida Atlantic University, Jupiter-FL, April 2015. [slides]
• Invited talk: “Image Processing and Computer Vision in iOS”, iOS Day, Universidade Federal do Triângulo Mineiro (UFTM), Uberaba, Brazil, December 2013. [slides]
• Colloquium: “Using games to improve computer vision solutions”, Alpen-Adria Universität Klagenfurt, Klagenfurt, Austria, May 2013. [slides]
• Invited talk: “Image retrieval: challenges and opportunities”, UTFPR, Curitiba-PR, Brazil, June 2012. [slides]
• Keynote speech: “Advances and Challenges in Visual Information Search and Retrieval”, 8^th Brazilian Computer Vision Workshop (WVC 2012) – Goiania-GO, Brazil, May 2012. [slides]
• Invited talk: “Mobile Visual Search”, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain, March 2012. [slides]
• Colloquium: “Recent Advances in Visual Information Retrieval”, Alpen-Adria Universität Klagenfurt, Klagenfurt, Austria, June 2010. [slides]
• Invited talk: “State of the art in image search and retrieval”, WISMA 2010, Barcelona, May 2010. [slides]

Slides and supporting materials for tutorials, seminar and short courses

• Tutorial (with Christian Garbin): “The Data Science landscape: foundations, tools, and practical applications”, 18^th IEEE International Conference on Machine Learning and Applications – ICMLA 2019, Boca Raton, Florida, USA, December 2019. [slides] [code]
• 4-lecture series: “Innovative Technologies for Everyday Life”, Lifelong Learning Society (LLS), Florida Atlantic University, Jan-Feb 2016.
  • A short book with expanded notes from the series is available on Amazon.
• 4-lecture series: “Social Media and Smartphones”, Lifelong Learning Society (LLS), Florida Atlantic University, October 2014.
  • Lecture notes (PDF)
• Mini-course: “Image Processing and Computer Vision in iPhone and iPad”, 7^th Brazilian Computer Vision Workshop (WVC 2011), Curitiba-PR, Brazil, May 2011. [slides]
• Tutorial: “Advances in Image Search and Retrieval”, IASTED International Conference on Internet and Multimedia Systems and Applications (IMSA) 2011, Washington, DC, May 2011. [slides]

Guided Tours

Since 2014, I have prepared a series of documents called “Guided Tours,” which consist of carefully curated material and cutting-edge resources, organized as a sequence of steps that provide a road map to guide students through concepts and technologies, allowing them to learn (more) about a specific language, software package or set of technologies with a systematic and confidence-building approach.

My Guided Tours contain links to numerous free resources, including tools, videos, and interactive tutorials. They are respectful of students’ learning style, allow self-paced learning, and include optional steps for those who want to go above and beyond.

Examples of Guided Tours include:

• A Guided Tour to JavaScript: guides students through the intricacies of the JavaScript programming language and its use in client-side development of web pages and web-based apps. [February 2016 PDF]
• A Guided Tour to PHP: helps students master the PHP programming language and the MySQL database management system, which are among the most popular environments for server-side development of web pages and web-based apps. [April 2016 PDF]
• A Guided Tour to Machine Learning Using MATLAB: teaches the basics of Machine Learning using the MATLAB scientific package and some of its toolboxes and apps, particularly the Classification Learner App. [April 2017 PDF]

Recommended books

This is a list of favorite/recommended books (see disclaimer below), roughly organized by category and sorted alphabetically by title.
It will be substantially updated over time. Check back often.

Artificial Intelligence, Machine Learning, Deep Learning

• Artificial Intelligence: A Guide for Thinking Humans – Melanie Mitchell (2019)
• Artificial Intelligence: A Modern Approach 3/e – Stuart Russell and Peter Norvig (2011)
• Deep Learning – Ian Goodfellow, Yoshua Bengio, and Aaron Courville (2016)
• Deep Learning Illustrated: A Visual, Interactive Guide to Artificial Intelligence – Jon Krohn, Grant Beyleveld, and Aglaé Bassens (2019)
• Deep Learning with Python – François Chollet (2017)
• Deep Learning with R – François Chollet (2018)
• Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems 2/e – Aurélien Géron (2019)
• Human Compatible: Artificial Intelligence and the Problem of Control – Stuart Russell (2019)
• Rebooting AI: Building Artificial Intelligence We Can Trust – Gary Marcus and Ernest Davis (2019)
• You Look Like a Thing and I Love You: How Artificial Intelligence Works and Why It’s Making the World a Weirder Place – Janelle Shane (2019)

Computer Vision, Image Processing, Image Analysis, Video Processing

• Computer Vision: Models, Learning, and Inference – Simon Prince (2012)
• Practical Image and Video Processing Using MATLAB – Oge Marques (2011)

Data Science

• Python Data Science Handbook: Essential Tools for Working with Data – Jake VanderPlas (2016)
• R for Data Science: Import, Tidy, Transform, Visualize, and Model Data – Hadley Wickham and Garrett Grolemund (2016)

Vision Science, Human Vision, Psychology of Vision, Visual Intelligence

• The Artist’s Eyes – Michael Marmor and James Ravin (2009)
• The Museum of Illusions: Optical Tricks in Art – Celine Delavaux (2013)
• Vision Science: Photons to Phenomenology – Stephen E. Palmer (1999)
• Visual Intelligence: Sharpen Your Perception, Change Your Life – Amy E. Herman (2016)

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