Zobrazeno 1 - 10
of 51
pro vyhledávání: '"Lim, JongYoon"'
Autor:
Johanson, Deborah L, Ahn, Ho Seok, MacDonald, Bruce A, Ahn, Byeong Kyu, Lim, JongYoon, Hwang, Euijun, Sutherland, Craig J, Broadbent, Elizabeth
Publikováno v:
Journal of Medical Internet Research, Vol 22, Iss 3, p e18362 (2020)
Externí odkaz:
https://doaj.org/article/134696f2d1c04bcf8fc08493ae3e81e8
This research explores using lightweight deep neural network architectures to enable the humanoid robot Pepper to understand American Sign Language (ASL) and facilitate non-verbal human-robot interaction. First, we introduce a lightweight and efficie
Externí odkaz:
http://arxiv.org/abs/2309.16898
Autor:
Qureshi, Ans, Smith, David, Gee, Trevor, Nejati, Mahla, Shahabi, Jalil, Lim, JongYoon, Ahn, Ho Seok, McGuinness, Ben, Downes, Catherine, Jangali, Rahul, Black, Kale, Lim, Hin, Duke, Mike, MacDonald, Bruce, Williams, Henry
Aotearoa New Zealand has a strong and growing apple industry but struggles to access workers to complete skilled, seasonal tasks such as thinning. To ensure effective thinning and make informed decisions on a per-tree basis, it is crucial to accurate
Externí odkaz:
http://arxiv.org/abs/2308.07512
Autor:
Xing, Yuning, Pham, Dexter, Williams, Henry, Smith, David, Ahn, Ho Seok, Lim, JongYoon, MacDonald, Bruce A., Nejati, Mahla
Publikováno v:
Proceedings of the Australasian conference on robotics and automation (ACRA 2022)
Smart farming is a growing field as technology advances. Plant characteristics are crucial indicators for monitoring plant growth. Research has been done to estimate characteristics like leaf area index, leaf disease, and plant height. However, few m
Externí odkaz:
http://arxiv.org/abs/2304.03610
Autor:
Qureshi, Ans, Loh, Neville, Kwon, Young Min, Smith, David, Gee, Trevor, Bachelor, Oliver, McCulloch, Josh, Nejati, Mahla, Lim, JongYoon, Green, Richard, Ahn, Ho Seok, MacDonald, Bruce, Williams, Henry
Following a global trend, the lack of reliable access to skilled labour is causing critical issues for the effective management of apple orchards. One of the primary challenges is maintaining skilled human operators capable of making precise fruitlet
Externí odkaz:
http://arxiv.org/abs/2302.09716
This paper presents datasets utilised for synthetic near-infrared (NIR) image generation and bounding-box level fruit detection systems. It is undeniable that high-calibre machine learning frameworks such as Tensorflow or Pytorch, and large-scale Ima
Externí odkaz:
http://arxiv.org/abs/2203.09091
Autor:
Lim, JongYoon, Sa, Inkyu, Ahn, Ho Seok, Gasteiger, Norina, Lee, Sanghyub John, MacDonald, Bruce
Publikováno v:
MDPI Sensors 2021, 21(8), 2712
Sentiment prediction remains a challenging and unresolved task in various research fields, including psychology, neuroscience, and computer science. This stems from its high degree of subjectivity and limited input sources that can effectively captur
Externí odkaz:
http://arxiv.org/abs/2104.09777
Autor:
Nejati, Mahla, Penhall, Nicky, Williams, Henry, Bell, Jamie, Lim, JongYoon, Ahn, Ho Seok, MacDonald, Bruce
Accurate and reliable kiwifruit detection is one of the biggest challenges in developing a selective fruit harvesting robot. The vision system of an orchard robot faces difficulties such as dynamic lighting conditions and fruit occlusions. This paper
Externí odkaz:
http://arxiv.org/abs/2006.11729
Autor:
Lim, JongYoon, Ahn, Ho Seok, Nejati, Mahla, Bell, Jamie, Williams, Henry, MacDonald, Bruce A.
In this paper, we present a novel approach to kiwi fruit flower detection using Deep Neural Networks (DNNs) to build an accurate, fast, and robust autonomous pollination robot system. Recent work in deep neural networks has shown outstanding performa
Externí odkaz:
http://arxiv.org/abs/2006.04343
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