Jesse Jensen

Tokyo

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Real-Time Ray Tracer
Built a real-time ray-tracer using OpenGL ES • Incorporated ambient, diffuse, specular, and reflective lighting • Simulated recursion iteratively in GLSL using a stack • Rendered models in a skybox to visualize reflection
Input-Corrective Drawing Pad
Created an input-corrective drawing tablet for those with disabilities that corrects shaky input and uses machine learning (Tensorflow) to classify handwriting • Carried project through engineering design process including stakeholder requirements, specifications document, engineering design, testing, verification, and result reports • Developed interactive art canvas UI • Corrected shaky user input using a line-smoothing algorithm that retained general shapes while correcting error • Engineered a convolutional neural network model in Tensorflow to achieve an accuracy of 98% when reading handwritten digits (approx. 93% from user input)

Ambition

未来

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