I am a software developer, wants to build a career in the Machine Learning field. I have work experience as a programmer and recently have experience in ML. I feel confident to learn something new and have an urge to improve myself.
Recently, I have finished my master's study in which I proposed a thesis about visual saliency by using different deep learning approaches. My focus in my work is a project on 3D object recognition along the assembly line. We come up with a Deep Learning solution for that problem. Basically, we train a proper DL architecture with renderings of 3D objects and try to reach high accuracy during inference which is conducted with real-time photographs of the objects. Within the scope of my thesis, I intend to apply the Generative Adversarial Network approach to the Visual Saliency topic. Very briefly, visual saliency is a field concerning people’s attention while seeing visual stimuli (an image or a frame in a video sequence) and visual saliency methods aim at reaching people’s eye fixations as much as possible. As a preliminary work of the visual saliency field, we published an article on the conference Cyberworlds 2019 and Computers and Graphics journal. After that, we enhanced our study and published a journal article titled "Deep into Visual Saliency for Immersive VR Environments Rendered in Real-time".
I am an easy-going and coherent person in a professional manner. I have experience in both working alone and working with a team. I know English as a foreign language.