METHOD FOR MEASURING CONCENTRATION OF BIOMETRIC MEASUREMENT OBJECT BY USING ARTIFICIAL INTELLIGENCE DEEP LEARNING

• 1. 利用人工智能深度学习的生物测量对象浓度测量方法 [P] . 中国专利： CN112105923A . 2020-12-18
• 2. 光生物测量装置及使用光生物测量装置的分析方法 [P] . 中国专利： CN104507396B . 2016.09.14
• 3. METHOD FOR MEASURING CONCENTRATION OF BIOMETRIC MEASUREMENT OBJECT BY USING ARTIFICIAL INTELLIGENCE DEEP LEARNING [P] . US2021285909A1 . 2021-09-16

  机译： 通过使用人工智能深入学习测量生物测量物体浓度的方法

• 4. METHOD FOR MEASURING CONCENTRATION OF BIOMETRIC MEASUREMENT OBJECT BY USING ARTIFICIAL INTELLIGENCE DEEP LEARNING [P] . 世界知识产权组织专利： WO2020013361A1 . 2020-01-16

  机译： 人工智能深度学习测量生物测量对象浓度的方法

• 5. CONSTRUCTION METHOD FOR ARTIFICIAL INTELLIGENCE ULTRA DEEP LAYER LEARNING MODEL, ARTIFICIAL INTELLIGENCE ULTRA DEEP LAYER LEARNING DEVICE, GENERAL PURPOSE MOBILE TERMINAL DEVICE ON WHICH ARTIFICIAL INTELLIGENCE ULTRA DEEP LAYER LEARNING MODEL IS MOUNTED, AND PROGRAM OF ARTIFICIAL INTELLIGENCE ULTRA DEEP LAYER LEARNING MODEL [P] . 日本专利： JP2018081684A . 2018-05-24

  机译： 用于人工智能超深层学习模型的人工智能超深层学习模型的构建方法，人工智能超深层学习设备，通用通用移动终端设备，程序

• 1. Innovative deep learning artificial intelligence applications for predicting relationships between individual tree height and diameter at breast height [J] . ilker Ercanli 森林生态系统：英文版 . 2020,第002期
• 2. Artificial Intelligence in Steam Cracking Modeling: A Deep Learning Algorithm for Detailed Effluent Prediction [J] . Pieter PPlehiers, Steffen HSymoens, Ismaël Amghizar, 工程（英文） . 2019,第006期
• 3. Quantum Machine Learning- Using Quantum Computation in Artificial Intelligence and Deep Neural Networks--Quantum Computation and Machine Learning in Artificial Intelligence [C] . Sayantan Gupta, Subhrodip Mohanta, Mayukh Chakraborty, Industrial Automation and Electromechanical Engineering Conference . 2017
• 4. Artificial Intelligence in the Assessment of Transmission and Distribution Systems under Natural Disasters Using Machine Learning and Deep Learning Techniques in a Knowledge Discovery Framework [D] . Arguelles, Rossana Villegas. 2019
• 5. Efficiency of a deep learning-based artificial intelligence diagnostic system in spontaneous intracerebral hemorrhage volume measurement [O] . Tao Wang, Na Song, Lingling Liu, 2021
• 6. Object Detection and Tracking using Deep Learning and Artificial Intelligence for Video Surveillance Applications [O] . HV Ravish 2019

• 1. Artificial Intelligence Driven Resiliency with Machine Learning and Deep Learning Components [J] . Bahman Zohuri ,Farhang Mossavar Rahmani . 通讯和计算机 . 2019,第001期
• 2. Research on the Application of Deep Learning in Artificial Intelligence Courses [J] . Ruijue Wang . 电子研究与应用 . 2021,第6期
• 3. Understanding deep learning in capsule endoscopy: Can artificial intelligence enhance clinical practice? [J] . Amporn Atsawarungruangkit ,Yousef Elfanagely ,Akwi W Asombang . 胃肠道内窥镜检查中的人工智能（英文） . 2020,第2期
• 4. 机制主义方法与人工智能统一理论——人工智能的新方法与新进展 [C] . 钟义信 . 2010年全国智能科学技术课程教学研讨会 . 2010
• 5. IOL Master与传统方法在眼生物测量及人工晶体计算的比较 [A] . 于鸣 . 2013