Computer Vision Developer

Functional Skills

Functional Skills are essential skills that help individuals perform tasks effectively in everyday life, work, and education.

Image Processing

Feature Extraction and Detection

Deep Learning Frameworks

Convolutional Neural Networks (CNNs)

Object Detection and Recognition

Image Segmentation

3D Computer Vision

Video Analysis

Model Optimization and Deployment

Data Augmentation

Transfer Learning

Python Programming

Soft Skills

Communication, teamwork, and critical thinking to ensure seamless project execution.

Problem-Solving

Communication

Attention to Detail

Continuous Learning

Collaboration

Time Management

Technical Skills

Technical Skills are specialized abilities and knowledge needed to perform specific tasks or functions.

Python Programming

OpenCV (Open Source Computer Vision Library)

Deep Learning Frameworks (TensorFlow, Keras, PyTorch)

Image Processing

Object Detection and Recognition

Machine Learning

Linear Algebra and Calculus

Data Analysis and Visualization

Cloud Computing (AWS, Azure, GCP)

Embedded Systems

C++ Programming

Robotics

Digital Image Processing

Statistical Pattern Recognition

Duties and Responsiblities

Task

95%

Develop and implement computer vision algorithms for image recognition, object detection, and image segmentation.

90%

Design and train deep learning models using frameworks like TensorFlow or PyTorch for computer vision applications.

85%

Optimize computer vision systems for performance and efficiency, especially for real-time applications.

80%

Collaborate with cross-functional teams to integrate computer vision solutions into larger products or systems.

75%

Conduct research and stay up-to-date with the latest advancements in computer vision and deep learning.

70%

Evaluate and benchmark different computer vision algorithms and techniques to select the best approach for a given problem.

65%

Implement and maintain data pipelines for collecting, cleaning, and labeling image and video data.

60%

Develop and maintain software libraries and tools for computer vision tasks.

55%

Write technical documentation and reports to communicate research findings and project outcomes.

50%

Participate in code reviews and contribute to improving the overall quality of the codebase.

Work Activities

95%

Design and implement computer vision algorithms for image and video analysis, crucial for core functionality.

92%

Train deep learning models using large datasets to improve accuracy and performance in various tasks.

90%

Clean, transform, and augment image and video data to prepare it for model training and evaluation.

88%

Integrate computer vision models into larger systems or applications, ensuring seamless operation.

85%

Optimize algorithms and models for speed and efficiency, especially for real-time applications.

82%

Conduct research to explore new computer vision techniques and improve existing methodologies.

80%

Write clean, efficient, and well-documented code for computer vision applications and tools.

78%

Test and validate computer vision systems to ensure reliability and accuracy in diverse conditions.

75%

Work with cross-functional teams to define requirements and integrate computer vision solutions.

72%

Create and maintain technical documentation for computer vision algorithms, models, and systems.

70%

Keep abreast of the latest advancements in computer vision and deep learning through research papers and conferences.

Detailed Work Profile

Interests