A proficient approach for face detection and recognition using machine learning and high‐performance computing

2021 ◽  
Author(s):  
Astha Singh ◽  
Shiv Prakash ◽  
Ankit Kumar ◽  
Divya Kumar
Keyword(s):  
Machine Learning ◽  
High Performance Computing ◽  
Face Detection ◽  
High Performance ◽  
Face Detection And Recognition ◽  
Performance Computing ◽  
Detection And Recognition

High-performance computing and machine learning applied in thermal systems analysis

2021 ◽  
Author(s):  
Mostafa Safdari Shadloo ◽  
Amin Rahmat ◽  
Larry K. B. Li ◽  
Omid Mahian ◽  
Avinash Alagumalai
Keyword(s):  
Machine Learning ◽  
High Performance Computing ◽  
Systems Analysis ◽  
High Performance ◽  
Thermal Systems ◽  
Performance Computing

Large-scale machine learning based on functional networks for biomedical big data with high performance computing platforms

2015 ◽  
Vol 11 ◽  
pp. 69-81 ◽  
Author(s):  
Emad Elsebakhi ◽  
Frank Lee ◽  
Eric Schendel ◽  
Anwar Haque ◽  
Nagarajan Kathireason ◽  
...  
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
High Performance Computing ◽  
High Performance ◽  
Large Scale ◽  
Functional Networks ◽  
Computing Platforms ◽  
Performance Computing

scholarly journals Reducing energy usage in resource-intensive Java-based scientific applications via micro-benchmark based code refactorings

2019 ◽  
Vol 16 (2) ◽  
pp. 541-564
Author(s):  
Mathias Longo ◽  
Ana Rodriguez ◽  
Cristian Mateos ◽  
Alejandro Zunino
Keyword(s):  
Machine Learning ◽  
High Performance Computing ◽  
Computer Simulations ◽  
High Performance ◽  
Machine Learning Algorithms ◽  
Energy Usage ◽  
Energy Aware ◽  
Scientific Application ◽  
Performance Computing ◽  
Reducing Energy

In-silico research has grown considerably. Today?s scientific code involves long-running computer simulations and hence powerful computing infrastructures are needed. Traditionally, research in high-performance computing has focused on executing code as fast as possible, while energy has been recently recognized as another goal to consider. Yet, energy-driven research has mostly focused on the hardware and middleware layers, but few efforts target the application level, where many energy-aware optimizations are possible. We revisit a catalog of Java primitives commonly used in OO scientific programming, or micro-benchmarks, to identify energy-friendly versions of the same primitive. We then apply the micro-benchmarks to classical scientific application kernels and machine learning algorithms for both single-thread and multi-thread implementations on a server. Energy usage reductions at the micro-benchmark level are substantial, while for applications obtained reductions range from 3.90% to 99.18%.

Face Detection and Recognition Using OpenCV

2021 ◽  
Vol 2 (2) ◽  
Author(s):  
Ramadan TH. Hasan ◽  
◽  
Amira Bibo Sallow ◽  
Keyword(s):  
Machine Learning ◽  
Computer Vision ◽  
Facial Expressions ◽  
Face Detection ◽  
Video Processing ◽  
Recognition Of Facial Expressions ◽  
Image And Video Processing ◽  
Gender And Age ◽  
Face Detection And Recognition ◽  
Detection And Recognition

Intel's OpenCV is a free and open-access image and video processing library. It is linked to computer vision, like feature and object recognition and machine learning. This paper presents the main OpenCV modules, features, and OpenCV based on Python. The paper also presents common OpenCV applications and classifiers used in these applications like image processing, face detection, face recognition, and object detection. Finally, we discuss some literary reviews of OpenCV applications in the fields of computer vision such as face detection and recognition, or recognition of facial expressions such as sadness, anger, happiness, or recognition of the gender and age of a person.

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