Computer Vision

Infosys • Full-time • Bengaluru East, IN • 2w ago

Deep Learning Frameworks: Proficiency in TensorFlow, PyTorch, or other deep learning libraries.
Computer Vision Tools: Expertise in OpenCV, Dlib, and other image processing libraries.
Model Deployment: Experience deploying models to production using platforms such as AWS, Google Cloud, or NVIDIA Jetson (for edge devices).
Algorithms: Strong understanding of core computer vision techniques like image classification, object detection (YOLO, Faster R-CNN), image segmentation (U-Net), and feature extraction.
Programming Languages: Proficient in Python, C++, and other relevant programming languages for computer vision tasks.
Data Handling: Experience working with large datasets, data augmentation, and preprocessing techniques.
Optimization: Skills in model optimization techniques such as pruning, quantization, and hardware acceleration (e.g., using GPUs or TPUs).
Stay up-to-date with the latest advancements in computer vision, deep learning, and AI, and apply this knowledge to push the boundaries of current solutions.
Conduct research to advance the field of computer vision, including contributing to the development of new algorithms, frameworks, or methodologies.
Design and implement novel computer vision models and algorithms for tasks such as object detection, image segmentation, optical character recognition (OCR), and facial recognition.
Utilize large datasets to train, test, and improve models, optimizing for both performance and efficiency.
Develop end-to-end computer vision pipelines, from data acquisition and preprocessing to model training, testing, and deployment.
Optimize models for both accuracy and real-time performance, leveraging tools such as TensorFlow, PyTorch, and OpenCV.
Experience with state-of-the-art computer vision techniques like GANs, reinforcement learning for vision tasks, and self-supervised learning.
Familiarity with edge-computing frameworks (e.g., TensorRT, NVIDIA DeepStream) for deploying models on embedded systems.
Contributions to open-source projects or published research papers in computer vision or related fields.

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