The best way to start a career is to closely study and work together with some of the best and brightest minds within your field of interest. Our summer internship is a great opportunity to get valuable, first-hand experience by working on interesting computer vision and machine learning projects.
Convolutional neural networks proved to be very effective for image processing, and are increasingly being used for sound processing. Indeed, by computing spectrograms of audio signals, we obtain visual representations of their spectrum of frequencies. These images can then be readily used in CNNs.
The goal of the internship is to make a brief review of the literature, implement a CNN for sound classification for an application of choice, and experiment with different hyperparameters, particularly those specific to audio data.
Required competencies: Python, TensorFlow, CNNs
Adverse weather conditions such as rain or snow can have a significant impact on autonomous driving performance. At the same time, such data can often be difficult to obtain. Therefore, advanced data augmentation techniques can be used to expand existing datasets. One of the newer approaches is to use a generative adversarial network (GAN) to generate synthetic data.
The goal of this project is to develop a GAN for generating adverse weather condition scenarios.
Required competencies: Python, machine learning basics, neural networks basics
Automatic emergency braking (AEB) is a staple of modern advanced driver-assistance systems. The purpose of AEB is to mitigate crashes by initiating braking automatically when hazardous conditions arise. Working with object tracking, it is often necessary to evaluate new solutions against introducing potentially false AEB situations.
The purpose of this internship is to explore the existing AEB algorithms in the available body of scientific work and to develop a custom algorithm and testing environment evaluating the potential for AEB activation on a given dataset and its resimulations given different changes in the object detection and tracking pipeline. The solution is expected to blend seamlessly with the existing environments using existing resimulation pipelines and build systems.
The algorithm should be implemented in Python using good industry code practices and developed through a version control system (Git). It is expected that the algorithm and the environment will go through a few iterations during the internship, each iteration bringing new improvements and features thus simulating the development of products in agile setups in order to showcase how development is done in industry.
Required competencies: Python
To apply for our summer internship, send your CV, motivational letter and the topic you’re interested in to firstname.lastname@example.org. If you have any questions, feel free to send them over as well. The applications are open until May 31.
At Visage Technologies, we develop smart solutions powered by computer vision and machine learning. A specialized division of the company – Automotive Division – exclusively collaborates with a major automotive safety supplier, developing algorithms for ADAS (Advanced Driver Assistance System). The system detects and tracks objects such as other vehicles and pedestrians, with applications such as automatic braking, lane keeping assistance, adaptive cruise control, etc.
Visage Technologies has been on Deloitte’s list of the fastest-growing technology companies since 2017. Our team keeps growing as well, so we’re often on the lookout for new colleagues.