Research:
Using realistic and convincing threat object insertion within 3D CT luggage pictures, researchers from IEEE demonstrated a method for 3D TIP in CT volumes. The suggested method includes the production of metal artifacts, particle swarm optimization-based insertion determination, and dual threat (source) and baggage (target) volume segmentation. To assess the quality of generated TIP volumes, they also proposed a TIP quality score metric. Qualitative assessments on actual 3D CT luggage images demonstrate the ability of their approach to produce plausible and realistic TIP that are indistinguishable from actual CT volumes, and the TIP quality scores are congruent with human assessments.
Deep neural networks have significantly improved the representational power available to researchers working on image-based 3D human shape prediction. Even while current methods have shown promise in practical situations, they are still unable to recreate the level of detail that is frequently found in the input photos. By creating a multi-level architecture that is end-to-end trainable, researchers at Facebook Reality Labs address this restriction. At a lower resolution, a coarse level monitors the entire scene and concentrates on systemic thinking. This gives context to a fine level which estimates very detailed geometry by observing higher-resolution photos. By completely using input photographs with a resolution of 1K, they show that their method greatly outperforms current state-of-the-art methods for reconstructing human shapes from a single image.
Open Source News:
Data warehousing and AI-based solutions are the main areas of concentration for Databricks, a software company that has made a name for itself in many different industries. As a result of ChatGPT's recent stratospheric rise, companies like Meta, Google, and even Mozilla have made comparable attempts. Furthermore, Databricks is currently making an effort in their own way by making its large language model (LLM), known as "Dolly," available for public use. Many of ChatGPT's features can also be demonstrated using Dolly.
After a significant open source software vulnerability was identified last year, senators on Thursday reintroduced bipartisan legislation to help safeguard the federal government and key infrastructure systems by ensuring that open source software used by them is secure. The Securing Open Source Software Act, which would mandate the Cybersecurity and Infrastructure Security Agency (CISA) to develop a risk framework to assess how open source software is used by the federal government, was reintroduced last week by Senators Josh Hawley, R-MO, and Gary Peters, D-MI, Chairman of the Homeland Security and Governmental Affairs Committee.