Ứng dụng học sâu (deep learning) để phát hiện xe máy trong giao thông

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Ứng dụng học sâu (deep learning) để phát hiện xe máy trong giao thông

Mục tiêu luận văn là ứng dụng phương pháp học sâu để phát hiện và nhận dạng xe máy trong các hình ảnh thu nhận từ camera.

Đã lưu trong:

Sonraí Bibleagrafaíochta
Príomhúdar:	Dương Mộng Thu
Údair Eile:	TS. Huỳnh Hữu Hưng
Teanga:	vie
Foilsithe:	Trường Đại học Trà Vinh 2020
Rochtain Ar Líne:	https://opac.tvu.edu.vn/pages/opac/wpid-detailbib-id-35357.html
Clibeanna:	Cuir Clib Leis Gan Chlibeanna, Bí ar an gcéad duine leis an taifead seo a chlibeáil!

Thư viện lưu trữ:	Trung tâm Học liệu – Phát triển Dạy và Học, Trường Đại học Trà Vinh

Míreanna Comhchosúla

Ứng dụng học sâu (deep learning) để phát hiện xe máy trong giao thông
le: Dương, Mộng Thu
Foilsithe: (2019)

Deep learning
le: Goodfellow, Ian
Foilsithe: (2016)

Deep learning
le: Goodfellow, Ian
Foilsithe: (2016)

Deep learning - Cuộc cách mạng học sâu
le: Sejnowski, Terrence J
Foilsithe: (2019)

Deep Learning Architectures
le: Calin, Ovidiu
Foilsithe: (2020)

Advances in Deep Learning
le: Wani, M. Arif, et al.
Foilsithe: (2020)

Introduction to Deep Learning
le: Skansi, Sandro
Foilsithe: (2020)

Applied Deep Learning
le: Michelucci, Umberto
Foilsithe: (2020)

Deep Learning in Healthcare
le: Chen, Yen-Wei, et al.
Foilsithe: (2020)

MATLAB Deep Learning
le: Kim, Phil
Foilsithe: (2020)

Deep Learning Pipeline
le: El-Amir, Hisham, et al.
Foilsithe: (2020)

Deep Learning with Azure
le: Salvaris, Mathew, et al.
Foilsithe: (2020)

Deep Learning Applications
le: Wani, M. Arif, et al.
Foilsithe: (2020)

Deep Learning: Algorithms and Applications
le: Pedrycz, Witold, et al.
Foilsithe: (2020)

Deep Learning: Concepts and Architectures
le: Pedrycz, Witold, et al.
Foilsithe: (2020)

Guide to Deep Learning Basics
le: Skansi, Sandro
Foilsithe: (2020)

Neural Networks and Deep Learning
le: Aggarwal, Charu C.
Foilsithe: (2020)

Practical MATLAB Deep Learning
le: Paluszek, Michael, et al.
Foilsithe: (2020)

Deep Learning Techniques for Music Generation
le: Briot, Jean-Pierre, et al.
Foilsithe: (2020)

Deep Reinforcement Learning with Guaranteed Performance
le: Zhang, Yinyan, et al.
Foilsithe: (2020)

Development and Analysis of Deep Learning Architectures
le: Pedrycz, Witold, et al.
Foilsithe: (2020)

Deep Learning Classifiers with Memristive Networks
le: James, Alex Pappachen
Foilsithe: (2020)

Deep Learning for Natural Language Processing
le: Goyal, Palash, et al.
Foilsithe: (2020)

Deep Learning in Mining of Visual Content
le: Zemmari, Akka, et al.
Foilsithe: (2020)

Deep In-memory Architectures for Machine Learning
le: Kang, Mingu, et al.
Foilsithe: (2020)

Deep Learning in Natural Language Processing
le: Deng, Li, et al.
Foilsithe: (2020)

Phân loại Cam ứng dụng kỹ thuật Deep learning :
le: Danh, Hoàng Hải
Foilsithe: (2020)

Deep Learning with Python. 1st ed.
le: Ketkar, Nikhil
Foilsithe: (2020)

Introduction to Deep Learning Business Applications for Developers
le: Vieira, Armando, et al.
Foilsithe: (2020)

Network Intrusion Detection using Deep Learning
le: Kim, Kwangjo, et al.
Foilsithe: (2020)

Deep Learning Techniques for Biomedical and Health Informatics
le: Dash, Sujata, et al.
Foilsithe: (2020)

Deep Learning-Based Approaches for Sentiment Analysis
le: Agarwal, Basant, et al.
Foilsithe: (2020)

Recent Advances in Big Data and Deep Learning
le: Oneto, Luca, et al.
Foilsithe: (2020)

Human Centric Visual Analysis with Deep Learning
le: Lin, Liang, et al.
Foilsithe: (2020)

Big Data Analysis and Deep Learning Applications
le: Zin, Thi Thi, et al.
Foilsithe: (2019)

MATLAB deep learning : with machine learning, neural networks and artificial intelligence
le: Kim, Phil
Foilsithe: (2017)

Deep Active Learning. 1st ed. 2018
le: Matsushita, Kayo
Foilsithe: (2020)

Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
le: Samek, Wojciech, et al.
Foilsithe: (2020)

Evolutionary Approach to Machine Learning and Deep Neural Networks
le: Iba, Hitoshi
Foilsithe: (2020)

Automatic Speech Recognition : A Deep Learning Approach
le: Yu, Dong
Foilsithe: (2014)