This code helps in getting the steering angle of self driving car. The inspiraion is taken from [Udacity Self driving car](https://github.com/udacity/CarND-Behavioral-Cloning-P3) module as well [End to End Learning for Self-Driving Cars](https://devblogs.nvidia.com/deep-learning-self-driving-cars/) module from NVIDIA
Amidst the numerical renaissance and the rise of AI, 3D object recognition is a rapidly developing field that offers huge potential. Edge technologies are the next evolution for tangible robotics and smart systems, but current algorithms and machine learning techniques throttle the capabilities of this emerging field. To train an AI, nothing short of a desktop GPU is required. Energy consumption is often through the roof, and relying on remote cloud technologies for data processing invites a ...
Gestures can have a major impact on laptops just like on mobile phones. This this project makes the life of people easier by performing various tasks using just certain gestures. On the other hand this can also be used in scenario where a patient is unable to move their body. In such a case this can be used to play games which will work as an exercise and also some fun for the patient's mundane life.
STU-NET: Stupid Neural Net as the acronym goes is a really bad attempt at making race car A.I . So the attempt is to have the car drift , slide and move with really high speed. Because mainstream self driving a.i is too normal.
Range anxiety is a major issue that discourages drivers from considering electric cars as an alternative mode of transportation to the standard combustion engine vehicle. This project aims to provide such drivers with an upper bound prediction of travel time if they were to use an electric vehicle based on their own driving habits. The goal is to help such drivers estimate whether it would be reasonable for them to consider this more environmentally-friendly alternative without significantly ...
Writing Cv ,Resumes and cover letter has become tiresome,
what about this, a web that collect your moves and achievements intellectually and build you profile from the analysis?
Employers are given your URl to check on your progress and validate your ability from there!,
this look trustful.
Built and trained a convolutional neural network for end-to-end driving in a simulator, using TensorFlow and Keras. Used optimization techniques such as regularization and dropout to generalize the network for driving on multiple tracks.
In this project I going to use OPENVINO toolkit, to spot birds that come and go. Although seems like a pure entertainment project, this setup can be used for spotting intruders on surveillance cameras and will be extended to notify the delivery events.
We have built an Elderly fall detection system to detect the fall - Real time. It is a compact device and wireless too. Inside the room and also in the bathrooms, we shall detect the fall and alert the care takers immediately.
We may face situations, when we may have to leave our car for some other drivers and we may not be present to monitor the driving conditions. We may also face a devastating situation where we meet with an accident, and we may need to analyse what exactly went wrong. In these cases, the only way out is to monitor the live data from a vehicle.
An AI Powered Humanoid robot with gesture, image, vocal recognition and interactive communication systems alongside individual identifications and repetitive analysis completely offline. Such that it can work on its own using self hardware and pretrained neural modules.
Sentry version 1.0 is a fully autonomous electric vehicle at 1/10 scale running the Jetson TX2 platform, on-board, with Intel RealSense and ZED cameras for perception. In addition, there is a Hokuyo 10-LX 2D Lidar pulling point cloud data with about 30m of accurate range. All the components are powered with custom cables and a 50k MAH power bank that has 12v and 20v outputs. Sentry utilizes a "Vedder" Electronic Speed Control Unit (VESC) which can be powered by any traditional RC battery.
Giv...
RocketML is a super fast scale-out system for both Training machine learning models and Pre-processing steps.
As data gets larger, machine learning steps gets slower making data scientists job tedious. A distributed system like RocketML shortens model training and processing tasks from days to minutes.
RocketML is built to stitch together a large number of powerful Xeon processors to scale efficiently. Every component of the software is tuned so that the system is pushed to the limits of A...
MADRaS: Multi-Agent DRiving Simulator is a multi-agent version of TORCS, a racing simulator popularly used for autonomous driving research by the reinforcement learning and imitation learning communities.
New reinforcement learning (RL) model for cooperative multiagent domainsThe goal is to speed up learning by sharing experience between agents, taking advantage of the parallel exploration conducted by cooperative agents in a multiagent setting. It builds upon previous work conducted in the field of transfer learning in RL and multiagent settings.