3D Model - Revision history

BPeat at 13:07, 16 June 2024

2024-06-16T13:07:07Z

BPeat at 12:17, 16 June 2024

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BPeat at 12:12, 16 June 2024

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BPeat at 03:41, 2 March 2024

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BPeat at 02:28, 7 July 2023

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BPeat at 13:54, 16 June 2023

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BPeat at 15:19, 4 June 2023

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BPeat at 11:53, 2 June 2023

2023-06-02T11:53:51Z

@@ Line 18: / Line 18: @@
 * [[Robotics]] ... [[Transportation (Autonomous Vehicles)|Vehicles]] ... [[Autonomous Drones|Drones]] ... [[3D Model]] ... [[Point Cloud]]
-* [[Simulation]] ... [[Simulated Environment Learning]] ... [[Minecraft]]: [[Minecraft#Voyager|Voyager]]
+* [[Simulation]] ... [[Simulated Environment Learning]] ... [[World Models]] ... [[Minecraft]]: [[Minecraft#Voyager|Voyager]]
 * [[Cybersecurity]] ... [[Open-Source Intelligence - OSINT |OSINT]] ... [[Cybersecurity Frameworks, Architectures & Roadmaps | Frameworks]] ... [[Cybersecurity References|References]] ... [[Offense - Adversarial Threats/Attacks| Offense]] ... [[National Institute of Standards and Technology (NIST)|NIST]] ... [[U.S. Department of Homeland Security (DHS)| DHS]] ... [[Screening; Passenger, Luggage, & Cargo|Screening]] ... [[Law Enforcement]] ... [[Government Services|Government]] ... [[Defense]] ... [[Joint Capabilities Integration and Development System (JCIDS)#Cybersecurity & Acquisition Lifecycle Integration| Lifecycle Integration]] ... [[Cybersecurity Companies/Products|Products]] ... [[Cybersecurity: Evaluating & Selling|Evaluating]]
 * [[Spatial-Temporal Dynamic Network (STDN)]]

@@ Line 18: / Line 18: @@
 * [[Robotics]] ... [[Transportation (Autonomous Vehicles)|Vehicles]] ... [[Autonomous Drones|Drones]] ... [[3D Model]] ... [[Point Cloud]]
-* [[Simulation]] ... [[Simulated Environment Learning]]
+* [[Simulation]] ... [[Simulated Environment Learning]] ... [[Minecraft]]: [[Minecraft#Voyager|Voyager]]
 * [[Cybersecurity]] ... [[Open-Source Intelligence - OSINT |OSINT]] ... [[Cybersecurity Frameworks, Architectures & Roadmaps | Frameworks]] ... [[Cybersecurity References|References]] ... [[Offense - Adversarial Threats/Attacks| Offense]] ... [[National Institute of Standards and Technology (NIST)|NIST]] ... [[U.S. Department of Homeland Security (DHS)| DHS]] ... [[Screening; Passenger, Luggage, & Cargo|Screening]] ... [[Law Enforcement]] ... [[Government Services|Government]] ... [[Defense]] ... [[Joint Capabilities Integration and Development System (JCIDS)#Cybersecurity & Acquisition Lifecycle Integration| Lifecycle Integration]] ... [[Cybersecurity Companies/Products|Products]] ... [[Cybersecurity: Evaluating & Selling|Evaluating]]
 * [[Spatial-Temporal Dynamic Network (STDN)]]

@@ Line 17: / Line 17: @@
 [https://www.google.com/search?q=3D+model+artificial+intelligence+deep+learning+deep+machine+learning+ML+AI ...Google search]
-* [[Robotics]] ... [[Transportation (Autonomous Vehicles)|Vehicles]] ... [[Autonomous Drones|Drones]] ... [[3D Model]] ... [[3D Simulation Environments]] ... [[Simulated Environment Learning]] ... [[Point Cloud]]
+* [[Robotics]] ... [[Transportation (Autonomous Vehicles)|Vehicles]] ... [[Autonomous Drones|Drones]] ... [[3D Model]] ... [[Point Cloud]]
 * [[Cybersecurity]] ... [[Open-Source Intelligence - OSINT |OSINT]] ... [[Cybersecurity Frameworks, Architectures & Roadmaps | Frameworks]] ... [[Cybersecurity References|References]] ... [[Offense - Adversarial Threats/Attacks| Offense]] ... [[National Institute of Standards and Technology (NIST)|NIST]] ... [[U.S. Department of Homeland Security (DHS)| DHS]] ... [[Screening; Passenger, Luggage, & Cargo|Screening]] ... [[Law Enforcement]] ... [[Government Services|Government]] ... [[Defense]] ... [[Joint Capabilities Integration and Development System (JCIDS)#Cybersecurity & Acquisition Lifecycle Integration| Lifecycle Integration]] ... [[Cybersecurity Companies/Products|Products]] ... [[Cybersecurity: Evaluating & Selling|Evaluating]]
 * [[Spatial-Temporal Dynamic Network (STDN)]]

@@ Line 111: / Line 111: @@
 * [https://arxiv.org/pdf/1712.01537.pdf O-CNN: Octree-based convolutional neural networks for 3D shape analysis | P. Wang, Y. Liu, Y. Guo, C. Sun, and X. Tong]
 ** [https://github.com/microsoft/O-CNN O-CNN |  P. Wang, Y. Liu, Y. Guo, C. Sun, and X. Tong | GitHub] repository contains the implementation of O-CNN and Aadptive O-CNN  ...built upon the Caffe framework and it supports octree-based convolution, deconvolution, pooling, and unpooling.
-* [https://arxiv.org/abs/1611.05009 OctNet: Learning Deep 3D Representations at High Resolutions | G. Riegler, A. Ulusoy, and A. Geiger] a representation for deep learning with sparse 3D data. In contrast to existing models, our representation enables 3D convolutional networks which are both deep and high resolution. Towards this goal, we exploit the sparsity in the input data to hierarchically partition the space using a set of unbalanced octrees where each leaf node stores a pooled feature representation. This allows to focus memory allocation and computation to the relevant dense regions and enables deeper networks without compromising resolution. OctNet uses efficient space partitioning structures (i.e. octrees) to reduce memory and compute requirements of 3D convolutional neural networks, thereby enabling deep learning at high resolutions.
+* [https://arxiv.org/abs/1611.05009 OctNet: Learning Deep 3D Representations at High Resolutions | G. Riegler, A. Ulusoy, and A. Geiger] a representation for deep learning with sparse 3D data. In contrast to existing models, our representation enables 3D convolutional networks which are both deep and high resolution. Towards this goal, we exploit the sparsity in the input data to hierarchically partition the space using a set of unbalanced octrees where each leaf node stores a pooled feature representation. This allows to focus [[memory]] allocation and computation to the relevant dense regions and enables deeper networks without compromising resolution. OctNet uses efficient space partitioning structures (i.e. octrees) to reduce [[memory]] and compute requirements of 3D convolutional neural networks, thereby enabling deep learning at high resolutions.
 ** [https://github.com/griegler/octnet OctNet | GitHub]

@@ Line 21: / Line 21: @@
 * [[Spatial-Temporal Dynamic Network (STDN)]]
 * [[Hyperdimensional Computing (HDC)]]
-* [[Video/Image]] ... [[Vision]] ... [[Colorize]] ... [[Image/Video Transfer Learning]]
+* [[Video/Image]] ... [[Vision]] ... [[Enhancement]] ... [[Fake]] ... [[Reconstruction]] ... [[Colorize]] ... [[Occlusions]] ... [[Predict image]] ... [[Image/Video Transfer Learning]]
 * [https://arxiv.org/pdf/1808.01462.pdf A survey on Deep Learning Advances on Different 3D Data Representations | E. Ahmed, A. Saint, A. Shabayek, K. Cherenkova, R. Das, G. Gusev, and D. Aouada] - extending 2D deep learning to 3D data is not a straightforward tasks depending on the data representation itself and the task at hand.
 * [https://www.forbes.com/sites/bernardmarr/2019/08/23/the-amazing-ways-youtube-uses-artificial-intelligence-and-machine-learning/#553d467a5852 The Amazing Ways YouTube Uses Artificial Intelligence And Machine Learning | Bernard Marr - Forbes]

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 |title=PRIMO.ai
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-|keywords=artificial, intelligence, machine, learning, models, algorithms, data, singularity, moonshot, Tensorflow, Google, Nvidia, Microsoft, Azure, Amazon, AWS
+|keywords=ChatGPT, artificial, intelligence, machine, learning, GPT-4, GPT-5, NLP, NLG, NLC, NLU, models, data, singularity, moonshot, Sentience, AGI, Emergence, Moonshot, Explainable, TensorFlow, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Hugging Face, OpenAI, Tensorflow, OpenAI, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Meta, LLM, metaverse, assistants, agents, digital twin, IoT, Transhumanism, Immersive Reality, Generative AI, Conversational AI, Perplexity, Bing, You, Bard, Ernie, prompt Engineering LangChain, Video/Image, Vision, End-to-End Speech, Synthesize Speech, Speech Recognition, Stanford, MIT |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
 |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
 }}
 [https://www.youtube.com/results?search_query=3D+model+artificial+intelligence+deep+learning+deep+machine+learning+ML+AI Youtube search...]