DEEP LEARNING FOR OBJECT DETECTION USING PILLARS

• 1. 使用支柱进行对象检测的深度学习 [P] . 中国专利： CN111160561A . 2020-05-15
• 2. 一种基于端到端深度学习进行对象一致性检测方法 [P] . 中国专利： CN107944443A . 2018-04-20
• 3. DEEP LEARNING FOR OBJECT DETECTION USING PILLARS [P] . 美国专利： US2020150235A1 . 2020-05-14

  机译： 使用支柱进行深度学习以进行对象检测

• 4. DEEP LEARNING BASED OBJECT DETECTION MODEL TRAINING METHOD AND AN OBJECT DETECTION APPARATUS TO EXECUTE THE OBJECT DETECTION MODEL [P] . KR20210051722A . 2021-05-10

  机译： 基于深度学习的对象检测模型训练方法和对象检测装置来执行对象检测模型

• 5. DEEP LEARNING BASED OBJECT DETECTION MODEL TRAINING METHOD AND AN OBJECT DETECTION APPARATUS TO EXECUTE THE OBJECT DETECTION MODEL [P] . KR102315311B1 . 2021-10-19

  机译： 基于深度学习的对象检测模型训练方法和对象检测装置来执行对象检测模型

• 1. Towards Collaborative Robotics in Top View Surveillance:A Framework for Multiple Object Tracking by Detection Using Deep Learning [J] . Imran Ahmed, Sadia Din, Gwanggil Jeon, 自动化学报：英文版 . 2021,第007期
• 2. Towards Collaborative Robotics in Top View Surveillance: A Framework for Multiple Object Tracking by Detection Using Deep Learning [J] . Imran Ahmed, Sadia Din, Gwanggil Jeon, 自动化学报（英文版） . 2021,第007期
• 3. Salient Object Detection from Multi-spectral Remote Sensing Images with Deep Residual Network [J] . Yuchao DAI, Jing ZHANG, Mingyi HE, 测绘学报（英文） . 2019,第002期
• 4. Salient Object Detection from Multi-spectral Remote Sensing Images with Deep Residual Network [J] . Yuchao DAI, Jing ZHANG, Mingyi HE, 测绘学报(英文版) . 2019,第002期
• 5. An evaluation of deep learning based object detection strategies for threat object detection in baggage security imagery [J] . Dhiraj, Jain Deepak Kumar Pattern recognition letters . 2019,第APRa期
• 6. Efficient Object Detection and Classification of Heat Emitting Objects from Infrared Images Based on Deep Learning [J] . Abeer D. Algarni Multimedia Tools and Applications . 2020,第19a20期
• 7. Object Detection Binary Classifiers methodology based on deep learning to identify small objects handled similarly: Application in video surveillance [J] . Perez-Hernandez Francisco, Tabik Siham, Lamas Alberto, Knowledge-Based Systems . 2020,第Apra22期
• 8. FPGA based Deep Learning Models for Object Detection and Recognition Comparison of Object Detection Comparison of object detection models using FPGA [C] . S.P. Kaarmukilan, Soumyajit Poddar, Amal Thomas K International Conference on Computing Methodologies and Communication . 2020
• 9. Evaluation of Synthetic Training Data and Training-Data-Augmentation Techniques for Object Detection in Ground-Penetrating Radar Data using Deep-Learning Models [D] . Ruggiero, Jean. 2021
• 10. A deep learning approach to automatic teeth detection and numbering based on object detection in dental periapical films [O] . Hu Chen, Kailai Zhang, Peijun Lyu, -1
• 11. EER-ASSL: Combining Rollback Learning and Deep Learning for Rapid Adaptive Object Detection [O] . 2020

• 1. Fast object detection based on binary deep convolution neural networks [J] . Siyang Sun12 ,Yingjie Yin12 ,Xingang Wang12 . 智能技术学报 . 2018,第004期
• 2. 陶瓷部件—使用PTW16XL进行原材料的共混,使用HAAKEMiniJet进行样品制作 [C] . AnsgarFrendel . 第十一届先进成型与材料加工技术国际研讨会 . 2014
• 3. 使用Plant Village进行深度学习和特征提取的植物病害检测 [A] . MOHAMETH FAYE . 2020