Artificial Intelligence

Get the most out of your training, scoring, algorithms and frameworks on Intel® architecture for Deep Learning and Artificial Intelligence.

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Mona M. created project Identifying Mosquito Species using Smart-phone camera

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Identifying Mosquito Species using Smart-phone camera

Mosquito borne diseases have been amongst the most important healthcare concerns since time. An important component in combating the spread of infections in any geographic region of interest has been to identify the type of species that are prevalent in that region. As of today, dedicated personnel are assigned in most (if not all nations) to trap samples and identify them. Unfortunately, the process of identifying the actual species of mosquito is currently a manual process requiring highly trained personnel to visually inspect each specimen one by one under a microscope to make the identification. In this paper, we propose a system to automate this process. Specifically, we demonstrate results of an experiment we conducted where learning algorithms were designed to process images of captured mosquito samples taken via a smart-phone camera in order to identify the actual species. Using a total sample size of 60 images that included 7 species collected by the Hillsborough County Mosquito and Aquatic Weed Control Unit (in the city of Tampa) our proposed technique using Random Forests achieved an overall accuracy of 83:3% in correctly identifying the species of mosquito with good precision and recall. While our proposed technique will greatly benefit the state-of-the-art in species identification, we also believe that common citizens can also use our proposed system to improve existing mosquito control programs across the globe.

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Luckeciano M. created project Deep Reinforcement Learning for Humanoid Robot Walking and Kicking

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Deep Reinforcement Learning for Humanoid Robot Walking and Kicking

In this project, we apply modern Deep RL algorithms for optimizing Walking Engine and Kicking in Soccer 3D Simulation. The parameter optimization of walking and kicking is a big challenge in Robocup Soccer 3D Simulation enviroment. Until last year, the walking and kicking parameters are optimized by CMA-ES algorithm (a variant of genetic algorithms). This algorithm does not scale for hundreds or thousands of parameters, and it's proved that the bigger the number of parameters, the better is kicking and walking. Now, the Soccer 3D community started to apply Neural Networks for model the kick engine, and the results are very impressive. Due this, we started a project for finding better architectures for model the kick and started to apply the same techniques in walking engine. We propose to learn the entire walking engine with these techniques, replacing the traditional Double Inverted Pendulum-based walking engine.

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Nikhil K. created project American Sign Language Translation using hand pose estimation

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American Sign Language Translation using hand pose estimation

Sign language translation has been a long standing computer vision problem. Almost all the approaches so far require special hardware for effective results. In this approach, hand pose estimation will be used to extract the locations of key points of a hand and then they will be fed as inputs to the encoder in the sequence to sequence model. Using CTC, the relevant hand pose vectors can be matched with corresponding translations. For the entire model to work, a large dataset of sign language is needed.

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Stephanie Essin (Intel)

I received a Masters of Science in Multimedia and Journalism at the University of Oregon in 2016. I have been with Intel since 2015, and work as the associate video producer for Intel Software TV.

United States

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Abhijeet Ambadekar

Fast track Airport Car Rental, Domestic Airport., Tiruvalluvar Nagar, Besant Nagar, Chennai, Tamil Nadu 600090, India

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Subham Tewari

RR Palace, Danish Nagar, Nagchoon Rd, Khattalwada, Kasal Pura, Khandwa, Madhya Pradesh 450001, India

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Apolinario (Sam) Ortega

founder of - making formula and calculator easy to find and use

Arizona, USA

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Haider Ali

I am Haider Ali from Pakistan, Graduated in BE Electronics Engineering from Iqra University Karachi. I am working in Ministry of Energy, Govt. of Pakistan. My research area is in Control Systems, PLC, SCADA, Micro-Controller, Electronics and Communication.

Islamabad, Pakistan

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Adnan Ahmed

Mysuru, Karnataka, India

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team 7

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Created: 11/06/2016

autonomous car collision detection system

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