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OpenCV VS Microsoft Academic Knowledge API

Compare OpenCV VS Microsoft Academic Knowledge API and see what are their differences

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OpenCV logo OpenCV

OpenCV is the world's biggest computer vision library

Microsoft Academic Knowledge API logo Microsoft Academic Knowledge API

Tap into the wealth of academic content in the Microsoft Academic Graph using the Academic Knowledge API:
  • OpenCV Landing page
    Landing page //
    2023-07-29
  • Microsoft Academic Knowledge API Landing page
    Landing page //
    2023-05-15

OpenCV features and specs

  • Comprehensive Library
    OpenCV offers a wide range of tools for various aspects of computer vision, including image processing, machine learning, and video analysis.
  • Cross-Platform Compatibility
    OpenCV is designed to run on multiple platforms, including Windows, Linux, macOS, Android, and iOS, which makes it versatile for development across different environments.
  • Open Source
    Being open-source, OpenCV is freely available for use and allows developers to inspect, modify, and enhance the code according to their needs.
  • Large Community Support
    A large community of developers and researchers actively contributes to OpenCV, providing extensive support, tutorials, forums, and continuously updated documentation.
  • Real-Time Performance
    OpenCV is highly optimized for real-time applications, making it suitable for performance-critical tasks in various industries such as robotics and interactive installations.
  • Extensive Integration
    OpenCV can easily be integrated with other libraries and frameworks such as TensorFlow, PyTorch, and OpenCL, enhancing its capabilities in deep learning and GPU acceleration.
  • Rich Collection of examples
    OpenCV provides a large number of example codes and sample applications, which can significantly reduce the learning curve for beginners.

Possible disadvantages of OpenCV

  • Steep Learning Curve
    Due to the vast array of functionalities and the complexity of some of its advanced features, beginners may find it challenging to learn and use effectively.
  • Documentation Gaps
    While the documentation is extensive, it can sometimes be incomplete or outdated, requiring users to rely on community forums or external sources for solutions.
  • Resource Intensive
    Some functions and algorithms in OpenCV can be quite resource-intensive, requiring significant processing power and memory, which can be a limitation for low-end devices.
  • Limited High-Level Abstractions
    OpenCV provides a wealth of low-level functions, but it may lack higher-level abstractions and frameworks, necessitating more hands-on coding and algorithm development.
  • Dependency Management
    Setting up and managing dependencies can be cumbersome, especially when integrating OpenCV with other libraries or on certain operating systems.
  • Backward Compatibility Issues
    With frequent updates and new versions, backward compatibility can sometimes be problematic, potentially breaking existing code when updating.

Microsoft Academic Knowledge API features and specs

  • Rich Dataset
    The Microsoft Academic Knowledge API provides access to a vast amount of academic data, including publications, authors, journals, and conferences, which can enhance research and academic analysis.
  • Advanced Search Capabilities
    The API offers advanced search features that allow users to conduct complex queries, providing detailed information and insights for specific research needs.
  • Graph-based Data
    Utilizes a graph-based approach for representing relationships among academic entities, aiding in the exploration of connections within academic research.
  • Regular Updates
    The API data is regularly updated, ensuring that users have access to the latest research publications and academic information.

Possible disadvantages of Microsoft Academic Knowledge API

  • Discontinuation
    The Microsoft Academic services have been phased out by the end of 2021, which limits long-term availability and support for the API.
  • Access Restrictions
    Users may face limitations or require specific authorization to access certain datasets, which can hinder seamless integration and usage.
  • Learning Curve
    The API requires users to have a certain level of technical expertise to implement and use effectively, posing challenges for individuals unfamiliar with API integration.
  • Limited Scope
    While comprehensive, the API's dataset may not cover every niche or new academic field exhaustively, potentially missing out on emerging research areas.

OpenCV videos

AI Courses by OpenCV.org

More videos:

  • Review - Practical Python and OpenCV

Microsoft Academic Knowledge API videos

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Category Popularity

0-100% (relative to OpenCV and Microsoft Academic Knowledge API)
Data Science And Machine Learning
NLP And Text Analytics
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Spreadsheets
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare OpenCV and Microsoft Academic Knowledge API

OpenCV Reviews

7 Best Computer Vision Development Libraries in 2024
From the widespread adoption of OpenCV with its extensive algorithmic support to TensorFlow's role in machine learning-driven applications, these libraries play a vital role in real-world applications such as object detection, facial recognition, and image segmentation.
10 Python Libraries for Computer Vision
OpenCV is the go-to library for computer vision tasks. It boasts a vast collection of algorithms and functions that facilitate tasks such as image and video processing, feature extraction, object detection, and more. Its simple interface, extensive documentation, and compatibility with various platforms make it a preferred choice for both beginners and experts in the field.
Source: clouddevs.com
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
OpenCV is an open-source computer vision and machine learning software library that was first released in 2000. It was initially developed by Intel, and now it is maintained by the OpenCV Foundation. OpenCV provides a set of tools and software development kits (SDKs) that help developers create computer vision applications. It is written in C++, but it supports several...
Source: www.uubyte.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
These are some of the most basic operations that can be performed with the OpenCV on an image. Apart from this, OpenCV can perform operations such as Image Segmentation, Face Detection, Object Detection, 3-D reconstruction, feature extraction as well.
Source: neptune.ai
5 Ultimate Python Libraries for Image Processing
Pillow is an image processing library for Python derived from the PIL or the Python Imaging Library. Although it is not as powerful and fast as openCV it can be used for simple image manipulation works like cropping, resizing, rotating and greyscaling the image. Another benefit is that it can be used without NumPy and Matplotlib.

Microsoft Academic Knowledge API Reviews

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Social recommendations and mentions

Based on our record, OpenCV seems to be more popular. It has been mentiond 60 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

OpenCV mentions (60)

  • Grasping Computer Vision Fundamentals Using Python
    To aspiring innovators: Dive into open-source frameworks like OpenCV or PyTorch, experiment with custom object detection models, or contribute to projects tackling bias mitigation in training datasets. Computer vision isn’t just a tool, it’s a bridge between the physical and digital worlds, inviting collaborative solutions to global challenges. The next frontier? Systems that don’t just interpret visuals, but... - Source: dev.to / 4 days ago
  • Top Programming Languages for AI Development in 2025
    Ideal For: Computer vision, NLP, deep learning, and machine learning. - Source: dev.to / 17 days ago
  • Why 2024 Was the Best Year for Visual AI (So Far)
    Almost everyone has heard of libraries like OpenCV, Pytorch, and Torchvision. But there have been incredible leaps and bounds in other libraries to help support new tasks that have helped push research even further. It would be impossible to thank each and every project and the thousands of contributors who have helped make the entire community better. MedSAM2 has been helping bring the awesomeness of SAM2 to the... - Source: dev.to / 5 months ago
  • 20 Open Source Tools I Recommend to Build, Share, and Run AI Projects
    OpenCV is an open-source computer vision and machine learning software library that allows users to perform various ML tasks, from processing images and videos to identifying objects, faces, or handwriting. Besides object detection, this platform can also be used for complex computer vision tasks like Geometry-based monocular or stereo computer vision. - Source: dev.to / 6 months ago
  • F1 FollowLine + HSV filter + PID Controller
    This library is used for image and video processing, offering functions for tasks like object detection, filtering, and transformations in computer vision. - Source: dev.to / 8 months ago
View more

Microsoft Academic Knowledge API mentions (0)

We have not tracked any mentions of Microsoft Academic Knowledge API yet. Tracking of Microsoft Academic Knowledge API recommendations started around Mar 2021.

What are some alternatives?

When comparing OpenCV and Microsoft Academic Knowledge API, you can also consider the following products

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Microsoft Bing Autosuggest API - Show users intelligent search suggestions with the Bing Autosuggest API from Microsoft Azure. Test out the autocomplete API to see how it works.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Amazon Comprehend - Discover insights and relationships in text

NumPy - NumPy is the fundamental package for scientific computing with Python

FuzzyWuzzy - FuzzyWuzzy is a Fuzzy String Matching in Python that uses Levenshtein Distance to calculate the differences between sequences.