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Driving AI Forward: Coohom Cloud’s Groundbreaking 2D and 3D Interior Data Solutions Revealed at CVPR 2024

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HANGZHOU, China, June 28, 2024 /PRNewswire/ — Coohom Cloud, a leading provider of data services and solutions for the AI industry, proudly unveiled its latest advancements in 2D and 3D interior dataset products at the Conference on Computer Vision and Pattern Recognition (CVPR) 2024. This preeminent event, held from June 17-21 in Seattle, brought together top researchers, scientists, and industry leaders to explore breakthroughs in computer vision, artificial intelligence, machine learning, deep learning, and much more.

Embodied intelligence emerged as a focal point at CVPR this year, representing an advanced field that merges computer vision, machine learning, and robotics. The demand for large-scale and high-quality datasets has become increasingly evident, whether for training humanoid robots or constructing robust AI models.

Coohom Cloud was established by Koolab Innovation Laboratory of MANYCORE TECH INC. in 2017, after realizing that many industries were on the verge of significant investments in high-quality data. MANYCORE TECH INC. is a leading global cloud based interior design software platform, Coohom Cloud leverages its parent company MANYCORE TECH INC.’s extensive indoor data resources, combined with high-performance rendering engines and advanced data processing technologies, to deliver realistic and physically accurate 2D and 3D interior datasets and services to the AI industry.

In 2018, MANYCORE TECH INC. collaborated with Imperial College London and the University of Southern California to introduce the InteriorNet, which was then the largest publicly available indoor scene dataset. Building upon this, the MANYCORE TECH INC.’s platform now generate over 400,000 3D designs daily and houses approximately 360 million 3D models, encompassing furniture, appliances, household items, and more. This forms a robust data foundation provided by Coohom Cloud for research in indoor environment understanding, 3D reconstruction, robotics simulation and beyond.

Regarding 2D image rendering technology, Coohom Cloud employs a proprietary rendering engine to capture image data in diverse indoor settings through adjusting camera parameters, path trajectories, lighting conditions, etc., resulting in 2D datasets in formats such as RGB, depth, semantic, normal, point cloud, and others. This capability allows Coohom Cloud to produce 300,000 sets of 2D datasets daily, serving as ample training materials for AI agents’ navigation, visual perception, and environmental understanding capabilities.

To provide cost-effective data service solutions, Coohom Cloud utilizes its self-developed data processing engine designed for efficient data transformation, converting the accumulated database into formats suitable for AI training. This data engine can offer more comprehensive support on the physical, diversity, and data labeling fronts.

Physical Enhancement: Embodied intelligence’s real-world interactive capabilities are a key indicator of its level of intelligence. Coohom Cloud integrates cutting-edge simulation platforms like NVIDIA Isaac Sim to create 3D environments with realistic physical properties, allowing robots to undergo extensive interaction testing within a virtual realm. This significantly reduces training costs, enhances training safety, and improves repeatability.

Environment Augmentation: Coohom Cloud’s environment enhancement tool enriches the complexity of virtual environments through model element diversification, material variations, as well as lighting adjustments, etc. to simulate the diversity and complexity of the real world, enhancing the adaptability and generalization ability of robots.

Segmentation & Annotation: Coohom Cloud utilizes advanced synthetic data generation techniques to customize segmentation and annotation data, supporting various labels such as semantics, materials, spatial states. This approach significantly enhances data processing efficiency and accuracy.

Moreover, Coohom Cloud remains committed to exploring additional possibilities and value for computer vision and the entire AI field through technological innovation and industry partnerships.

About MANYCORE TECH INC.

MANYCORE TECH INC. is a leading global cloud based interior design software platform founded in November 2011. Specializing in the development and application of cloud based design software systems, the company aims to “Realizing Imagination”. MANYCORE TECH INC. provides software products and digital solutions for design rendering, marketing display, production integration, and construction implementation in home decoration, commercial spaces, and real estate construction. The company’s focus on cutting-edge research in computer graphics and AI has resulted in multiple research papers being selected for top international academic conferences such as SIGGRAPH Asia, CVPR, ECCV, and BMVC.

About Coohom Cloud

Coohom Cloud is a professional data service provider incubated by the parent company, MANYCORE TECH INC.’s innovation laboratory in 2017. Building upon the outstanding interior design digital assets of the parent company globally, Coohom Cloud offers an array of dataset services, including interior synthetic data generation and 3D virtual assets creation. This aims to accelerate the advancement of diverse industries such as AIGC, Robotics, AI Agents, XR and more. 

For more information, please visit or follow us on:
Contact: cloud@coohom.com
Website: www.coohomcloud.com
LinkedIn: www.linkedin.com/company/coohomcloud
X: x.com/Coohom_Cloud

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SOURCE MANYCORE TECH INC.

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Earth’s pulse monitored: a review highlights remote sensing time series progress

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As urbanization accelerates and environmental dynamics shift, the need for accurate and timely terrestrial monitoring has never been more urgent. A review has introduced a novel approach to remote sensing time series analysis, integrating multi-source data to enable near real-time monitoring. This innovative methodology promises to transform environmental conservation and urban planning by providing unprecedented insights into terrestrial changes and offering a more precise understanding of environmental dynamics.

GUANGZHOU, China, Dec. 22, 2024 /PRNewswire-PRWeb/ — An international team of researchers from South China Normal University, the University of Connecticut, and the Chinese Academy of Sciences has made a significant breakthrough in remote sensing. Their review, published (DOI: 10.34133/remotesensing.0285) in the Journal of Remote Sensing on December 11, 2024, addresses key challenges in remote sensing, such as incomplete data and noise interference. The team’s new time series analysis technique leverages advanced data reconstruction and fusion methods, significantly enhancing the precision and efficiency of remote sensing for monitoring environmental changes.

The research team has developed an advanced time series analysis technique that combines deep learning algorithms with traditional remote sensing methods to integrate data from various remote sensing sources. This innovative approach allows for the extraction of subtle patterns from large, complex datasets, which is crucial for monitoring critical environmental parameters such as land use and vegetation health. Unlike conventional techniques that struggle with incomplete or noisy data, this new methodology offers enhanced accuracy and more reliable insights into terrestrial dynamics, paving the way for more effective environmental monitoring.

Central to the study’s success is the integration of Long Short-Term Memory (LSTM) networks and Generative Adversarial Networks (GANs) to address the challenges posed by missing or noisy data. The LSTM networks capture temporal trends over time, while the GANs generate synthetic data that mimics real-world observations to fill gaps and correct for atmospheric distortions. This dual approach has resulted in a cleaner, more accurate time series dataset, which was validated against independent ground truth measurements. The researchers demonstrated significant improvements in key vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), setting a new benchmark in the field of remote sensing.

Experts in the field have lauded the study’s potential to revolutionize remote sensing applications. They see the method as a transformative tool for enhancing high-resolution monitoring and extending its coverage, particularly in agricultural surveillance, urban planning, and environmental management. “This method represents a crucial advancement in our ability to monitor environmental changes,” says Professor Fu. “As it evolves, it could play a key role in addressing climate change and other global challenges.”

The methodology’s future applications are vast, especially in global environmental monitoring and supporting sustainable development goals. By integrating multi-temporal data from Landsat and Sentinel-2 satellites, the team has created a framework for accurate and continuous terrestrial analysis. As computational power advances and algorithms improve, this technology is expected to become a vital tool for natural resource management, disaster response, and climate change mitigation. In the years to come, it could provide critical data to help policymakers address pressing environmental issues on a global scale.

References

DOI

10.34133/remotesensing.0285

Oiginal Source URL

https://doi.org/10.34133/remotesensing.0285

Funding information

This work was supported by the National Nature Science Foundation of China (grant numbers 42425001 and 42071399).

About Journal of Remote Sensing

The Journal of Remote Sensing, an online-only Open Access journal published in association with AIR-CAS, promotes the theory, science, and technology of remote sensing, as well as interdisciplinary research within earth and information science.

Media Contact

George Hua, Chuanlink Innovations, 1 8656606278, TranSpread1@gmail.com, http://chuanlink-innovations.com/

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SOURCE Journal of Remote Sensing

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ZINZINO AB (PUBL.): ENTERS INTO AGREEMENT TO PROVIDE DIP FINANCING TO ZURVITA INITIATING CHAPTER 11 PROCESS

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GOTHENBURG, Sweden, Dec. 22, 2024 /PRNewswire/ — Zinzino has in a press release dated 20240617 announced that a letter of intent to acquire 100% of the shares in the North American direct selling company Zurvita Inc. “Zurvita or the Company” was signed. Since then, Zinzino has negotiated with the owners of Zurvita Inc. and instead concluded that the purchase of Zurvita’s assets in a Chapter 11 proceeding for the Company is in Zinzino’s best interest.

Zinzino is providing a debtor-in-possession (DIP) financing to Zurvita, which filed for Chapter 11 bankruptcy proceedings on the 20th December 2024. By entering as a financier in Zurvita’s Chapter 11 with loans totaling USD 4.5 million, Zinzino simultaneously makes an offer to acquire the company’s assets via a so-called stalking horse bid. If the bid is accepted, the DIP loan will be converted into part of a debt-settled purchase price, which will be determined after Zurvita has completed the sale process that is subject to higher and better offers in accordance with the applicable terms of Chapter 11. Other bidders have the right to submit bids for Zurvita during the process and if another bid is accepted, Zinzino’s loan will be repaid and certain of its costs associated with the process will be reimbursed. 

Zurvita is a direct selling health company with operations in the United States, Canada and Mexico. The brand portfolio offers a range of innovative health and wellness products. The business has total annual sales of approximately USD 30 million with good gross margins. A potential transaction with Zinzino is expected to add growth through the synergies arising from the joint networks, combined with Zinzino’s test-based product concept. The profitability of the Company will thus be able to develop well by utilizing Zinzino’s existing technical platform and organization.

A visionary mindset, tech first perspective, test-based nutrition at the cellular level and a strong position to capitalize on current trends will form the basis of the new partnership. Following the acquisitions of VMA Life in 2020, Enhanzz in 2022, the strategic partnership with ACN and the recently completed asset acquisition of Xelliss, Zinzino has been looking for further strong investments to maintain its sustainable, profitable growth, strengthen its distribution power, expand into new markets and leverage the product portfolio in new consumer areas.

– “Individualized advice and tailored solutions are the future, and not just in health and wellness,” says Dag Bergheim Pettersen, CEO of Zinzino. “Together, we have years of combined industry experience and everything it takes to drive the modern, personalized shopping experience through direct sales”. Jay Shafer, CEO and co-founder of Zurvita, states “After considering multiple options for the company and under the guidance of our attorneys and third-party advisors, we feel this presents the best opportunity to continue Zurvita’s mission, deliver the highest quality products, and provide continuity for our staff and consultants. We are excited to see what the future holds for Zurvita.” 

For more information:
Dag Bergheim Pettersen CEO Zinzino +47 (0) 932 25 700, www.zinzino.com

Pictures for publication free of charge:
marketing@zinzino.com

Certified Adviser:
Carnegie Investment Bank AB (publ.)

Zinzino AB (publ.) is obliged to publish this information in compliance with current EU regulations governing market abuse. The information was provided by the above contact person for publication at 20.00 on the 21st of December 2024.

This information was brought to you by Cision http://news.cision.com

https://news.cision.com/zinzino/r/zinzino-ab–publ–enters-into-agreement-to-provide-dip-financing-to-zurvita-initiating-chapter-11-pr,c4086040

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Meet With Culture: Exquisite Craftsmanship of Traditional Chinese Architecture

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BEIJING, Dec. 22, 2024 /PRNewswire/ — The Temple of Agriculture in Beijing played a significant role during the Ming (1368-1644) and Qing (1644-1911) dynasties. Over nearly 600 years, 25 emperors personally visited or sent ministers to perform spring farming ceremonies and offer sacrifices to Shennong, the god of agriculture.

 

Built in 1420 during the Yongle reign, the temple’s predecessor was the Temple of Mountains and Rivers in Nanjing. When Emperor Zhu Di moved the Ming capital to Beijing, he constructed a larger temple inspired by the Nanjing temple, which gradually evolved into the Temple of Agriculture.

The Taisui Hall, the largest building complex in the temple, now serves as a major exhibition hall of the Beijing Ancient Architecture Museum, showcasing models of classical Chinese buildings and demonstrating the solemnity of royal architecture.

Ancient Chinese architecture is predominantly wooden-structured, chosen for its availability, versatility, and earthquake resistance. Artisans developed sophisticated techniques in material selection and construction. The wooden framework consists of columns, beams, girders, and purlins, with innovative structural forms like lifting-beam and piercing-bracket structures.

A unique architectural element is the dougong (bracket sets), which supports weight and connects beam frames with column walls. Mortise-tenon joints were invented to create elastic frameworks by connecting different components.

While discussing the Temple of Agriculture, it’s worth noting another remarkable example of architectural hierarchy which could be found in the Temple of Heaven. The hierarchy of architectural designs reflected social stratification, with eave structures like the triple-layered eaves of the Hall of Prayer for Good Harvest representing the highest-level architectural design.

Over centuries, the Temple of Agriculture has transformed from an imperial garden to a public park and a museum for historical architecture, now standing as a significant cultural landmark that symbolizes China’s agricultural civilization and architectural heritage along Beijing’s Central Axis.

Quickly join Alexandre to study and explore the traditional Chinese architecture.
https://youtu.be/YpA03WiZ9Wc

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SOURCE China International Communications Group

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