Computer Vision Internship
4 weeks ago
About the internship:Selected intern's day-to-day responsibilities include:
1. Develop and implement computer vision algorithms and deep learning models to solve complex problems in image and video analysis, object recognition, detection, segmentation, tracking, and other related tasks
2. Design and optimize neural network architectures for computer vision applications, leveraging state-of-the-art techniques and frameworks such as TensorFlow, PyTorch, OpenCV, R-CNN, Fast R-CNN, Faster R-CNN, and YOLO or Keras.
3. Conduct thorough research and stay updated with the latest advancements in computer vision and deep learning domains, including new algorithms, architectures, and datasets
4. Collaborate with cross-functional teams, including software engineers, data scientists, and domain experts, to understand project requirements, propose solutions, and integrate computer vision capabilities into our products
5. Pre-process, clean, and augment large-scale image and video datasets to train and fine-tune deep learning models, ensuring high performance and generalization
6. Analyze and evaluate the performance of computer vision models using appropriate evaluation metrics and techniques and iterate on the models to achieve desired outcomes
7. Collaborate with software engineers to integrate computer vision systems into production environments
>
Only those candidates can apply who:
1. are available for full time (in-office) internship
2. can start the internship between 18th Apr'24 and 23rd May'24
3. are available for duration of 3 months
4. have relevant skills and interests
Women wanting to start/restart their career can also apply.
Stipend:INR ₹ 15,000 /month
Deadline: :59:59
Other perks:Certificate, Letter of recommendation, Flexible work hours, Informal dress code
Skills required:MATLAB, OpenCV, Python, Machine Learning, Image Processing, Computer Vision, Neural Networks and Deep Learning
About Company:We deliver business growth by providing AI-powered data enrichment. Currently working in stealth mode.
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