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A robot machine that unites aesthetics, and technology in hair care is now in the PHL

by with No Comment BusinessTechnology

BMPlus January 1, 2024, 2 minute read

Now there’s a way to minimize the effects of hair loss and bald spots in men and women. Hair loss often translates to the loss of confidence, sometimes with devastating results. There are very few treatments that successfully bring hair back or reduce hair loss and the results are often temporary.

“Help is on the way for those who are experiencing bald spots and hair loss. At the forefront of technology, we are bringing Scatter to the Philippines as an innovative, affordable, simple, and safe solution to these issues,” assured Michael Hortaleza, CEO of MOHS Dermatology, the exclusive distributor of Scatter in the Philippines.“

Scatter, the groundbreaking way of minimizing the unsightly effects of bald spots and hair loss, was introduced at the 11th Annual Convention of the Philippine Academy of Aesthetics and Age Management Medicine Inc. (PAAAMI).

Eddy Kim, inventor and owner of Scatter and master Scatter from Korea, conducted a live demo and lecture, providing attendees with a firsthand look at this transformative technology. In his demonstration, Kim showed how the Scatter machine can be used here in the Philippines.  “Scatter is the blending of art and technology,” remarked Kim. 

The Scatter machine is an innovative Scalp Micropigmentation Technology from Korea that combines computer technology with the art and science of aesthetics.

Essentially, Scatter is programmed like a computer to tattoo hair-like spots on the scalp to darken bald spots and areas of thinning hair. The spots are precisely placed so that they simulate actual hair to give the illusion of a full head of hair.

Scatter treatment will be available at select dermatologists, who will receive the necessary training to use this game-changing technology.

MOHS Dermatology is the professional dermatology arm of MOHS Analytics, a fast-growing diversified company that prides itself on providing quality health and wellness solutions through technology that addresses what is needed by Filipinos nationwide.

Mike Hortaleza, Arkana, Neuroscience in Skincare, Neurocosmetics

Introducing Neuroscience in Skincare: Arkana by MOHS Dermatology

by with No Comment BusinessTechnology

By Manila Standard Business

MOHS Dermatology, the fast-growing professional dermatology arm of MOHS Analytics, has introduced Arkana Neurocosmetics into the Philippine market. The introduction of high-quality neuro-cosmetics skincare products marks MOHS Dermatology’s dedication to the convergence of neuroscience and skincare.

A trusted European skincare brand, Arkana is at the forefront of the emerging field of neurocosmetics This discipline focuses on understanding the brain-skin connection to develop products that optimally enhance skin health. By incorporating neuroscientific principles into skincare, Arkana’s neuro-cosmetics range promises a deeper level of skin nourishment and rejuvenation.

“Neurocosmetics, which fuses science and beauty, set Arkana apart from other derma products,” says Evelyn Santiago, MOHS marketing manager. “Arkana’s potent line of skin care products uses the body’s neurotransmitters to signal how the body should repair and enhance the skin, ensuring greater safety and effectiveness.”

Arkana’s dedication to neurocosmetics underlines a commitment to progressive skincare solutions deeply rooted in scientific research and innovation. By integrating the latest advancements in neuroscience into skincare, Arkana offers skincare products that are not only effective but also at the cutting edge of scientific understanding.

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Arkana’s extensive range of products is meticulously crafted in Europe to cater to a myriad of skin types, spanning all ages and addressing various skin concerns. With over 200 scientifically developed products, each built upon more than 80 original cosmetic formulas, Arkana has developed a collection of products that guarantees a perfect match for every individual.

Arkana understands that each skin is different and needs a unique treatment regimen. Available only through dermatologists, Arkana’s wide-ranging product selection is designed to seamlessly align with diverse preferences and requirements. Whether a person is navigating the nuances of aging, grappling with specific skin issues, or seeking products tailored to their skin type, dermatologists will help their patients find a suitable Arkana product that will meet or exceed their expectations. Committed to neurocosmetics, Arkana is redefining the boundaries of effective skincare, making its users achieve the beautiful skin they deserve.

Arkana is exclusively imported by MOHS Dermatology, the professional dermatology arm of MOHS Analytics, a fast-growing diversified company that prides itself on providing quality health and wellness solutions through technology that addresses what is needed by Filipinos nationwide.

Introducing Neuroscience in Skincare: Arkana by MOHS Dermatology
OCRTECH

Revolutionizing and Creating a Smart Manufacturing Assembly Line with Object Detection: A Deep Dive into Object Detection with Machine Learning and OpenCV

by with No Comment Technology

by: Christopher Polo Gabriel

Introduction

In the fast-paced world of manufacturing, efficiency and quality control are critical. This comprehensive blog explores the integration of Object Detection using machine learning and OpenCV technology in a manufacturing assembly line. In the realm of modern manufacturing, optimizing and ensuring product quality are paramount. This blog explores the integration of Object Detection using machine learning and OpenCV technology in a manufacturing assembly line. The goal is to create a system that not only monitors, counts, checks, and validates products seamlessly.

Understanding Object Detection

Object detection, a computer vision technique, empowers software systems to detect, locate, and trace objects within images or videos. Object Detection identifies and classifies specific objects within images or videos. In manufacturing, this technology revolutionizes the traditional manual counting and tallying processes. Let’s dive into how it can transform the manufacturing landscape.

Object Detection in Action

  • Automated Counting: Implementing neural networks allows the system to decide counting templates automatically, enhancing accuracy and speed, Utilizing neural networks for automated counting enhances accuracy and speed.
  • Quality Assurance: Object Detection can distinguish between good and faulty parts, enabling timely corrective actions. Leveraging pre-trained models ensures robust validation of the product.
  • Validation with Pre-Trained Models and OCR Technologies:  Object Character Recognition (OCR) can be employed to identify characters on printed stickers, ensuring accurate validation, Using a trained Libraby also validates the information feed to the machine.

Implementing OpenCV Technology

  • OpenCV, a powerful open-source computer vision and machine learning library, plays a pivotal role in developing the Object Detection system. Its capabilities include image processing, and a machine learning software library, which is instrumental in developing the Object Detection system and feature detection capabilities.

Building the System

  • Data Collection: Gather a diverse dataset of product images and videos to train the Object Detection model.
  • Model Training: Use machine learning algorithms to train the model to recognize, identify, and classify different products accurately.
  • Integration with Assembly Line: Implement the trained model into the manufacturing assembly line for real-time monitoring and decision-making.
  • Integration with the system: Create a system that pulls the data coming from the object detection application, and creates some sort of analytic dashboard to see the overview in realtime.

Image Preprocessing Using OpenCV

  • Explore how OpenCV is employed for image preprocessing in the context of manufacturing and other industries related to the process.
  • The Impact of AI in Manufacturing
  • Reach into the broader implications of artificial intelligence, including computer vision, in the manufacturing sector and other industries with the same processes.

Benefits and Challenges

  • Discuss the benefits of integrating Object Detection in manufacturing, addressing potential challenges, and how to overcome them.
  • Enhanced Efficiency: Automated processes reduce manual intervention, enhancing overall production efficiency.
  • Improved Accuracy: Object Detection minimizes errors associated with manual counting and validation.
  • Cost Savings: Long-term cost savings are achieved through reduced manual labor and increased production efficiency.

Future Trends

  • Explore emerging trends in Object Detection and machine learning that could further enhance manufacturing processes.
  • Integration of AI in Manufacturing: The use of Artificial Intelligence (AI) and Machine Learning (ML) in manufacturing is set to grow, enhancing efficiency and decision-making in processes such as quality control and product validation.
  • AI-Based Cybersecurity: Machine Learning techniques will play an increasing role in detecting and responding to cybersecurity threats, ensuring the security of manufacturing systems.
  • Advancements in Machine Learning Technology: Ongoing innovations in machine learning technology will impact various aspects of business operations, offering new opportunities for optimization in manufacturing processes.
  • Evolution in Object Recognition: Machine Learning techniques for object recognition, as discussed in recent studies, are evolving, showing potential in recognizing objects and features in manufacturing processes.
  • Tiny ML and MML Trends: Emerging trends like Tiny ML (deploying machine learning models on edge devices) and MML (Model Management Layer) are anticipated to play a significant role in shaping the future of machine learning applications, including manufacturing.
  • Advancements in Computer Vision: The future of computer vision, a crucial component of object detection, is marked by continuous advancements, transforming industries such as manufacturing through improved image recognition and analysis.

Conclusion

This large-scale exploration of Object Detection with machine learning and OpenCV displays the transformative potential for manufacturing assembly lines. By merging advanced technologies, manufacturers can achieve unparalleled levels of efficiency, accuracy, and quality control also with machine learning and OpenCV technology in a manufacturing assembly line transfigure the traditional processes and cost-effectiveness in the long term.

Sources

This blog serves as a guide for manufacturers looking to embrace the future of smart manufacturing, i would like to thank the sources for making this blog possible.