Zobrazeno 1 - 10
of 393
pro vyhledávání: '"Jiun-In Guo"'
Publikováno v:
Sensors, Vol 24, Iss 17, p 5737 (2024)
In the field of automatic optical inspection (AOI), this study presents innovative strategies to enhance object detection accuracy while minimizing dependence on large annotated datasets. We initially developed a defect detection model using a datase
Externí odkaz:
https://doaj.org/article/dc09fba0361c40e794f71efe04607a4d
Autor:
Vinay Malligere Shivanna, Jiun-In Guo
Publikováno v:
Sensors, Vol 24, Iss 1, p 249 (2023)
Advanced driver assistance systems (ADASs) are becoming increasingly common in modern-day vehicles, as they not only improve safety and reduce accidents but also aid in smoother and easier driving. ADASs rely on a variety of sensors such as cameras,
Externí odkaz:
https://doaj.org/article/08c012e46d7f4f4caeb28d2e16b4b005
Publikováno v:
IEEE Access, Vol 10, Pp 51458-51471 (2022)
This paper proposes an improvement to the multi-object tracking system framework based on the image inputs. By analyzing the role and performance of each block in the original multi-objects tracking system, the blocks of the original system are recon
Externí odkaz:
https://doaj.org/article/57c1242c9af84a86b146df5ee94f964b
Publikováno v:
Sensors, Vol 23, Iss 12, p 5560 (2023)
This paper proposes the design of a 360° map establishment and real-time simultaneous localization and mapping (SLAM) algorithm based on equirectangular projection. All equirectangular projection images with an aspect ratio of 2:1 are supported for
Externí odkaz:
https://doaj.org/article/08b0df24bee04446853770b759fe96ff
Publikováno v:
Sensors, Vol 23, Iss 5, p 2746 (2023)
This paper proposes a deep learning-based mmWave radar and RGB camera sensor early fusion method for object detection and tracking and its embedded system realization for ADAS applications. The proposed system can be used not only in ADAS systems but
Externí odkaz:
https://doaj.org/article/bd15db974849444b82c84adf7947b961
Publikováno v:
IEEE Access, Vol 9, Pp 50700-50714 (2021)
This paper presents a lightweight Multi-task Semantic Attention Network (MTSAN) to collectively deal with object detection as well as semantic segmentation aiding real-time applications of the Advanced Driver Assistance Systems (ADAS). This paper pro
Externí odkaz:
https://doaj.org/article/48b135a0847e4cbd8bce04b535b56deb
Autor:
Zohauddin Ahmad, Yan-Min Liao, Sheng-I Kuo, You-Chia Chang, Rui-Lin Chao, Naseem, Yi-Shan Lee, Yung-Jr Hung, Huang-Ming Chen, Jyehong Chen, Jiun-In Guo, Jin-Wei Shi
Publikováno v:
IEEE Access, Vol 9, Pp 85661-85671 (2021)
In this work, we demonstrate the high-power and high-responsivity performance of the dual multiplication (M-) layers in In0.52Al0.48As based avalanche photodiode (APD). The dual M-layer design in our APD structure effectively constrains the multiplic
Externí odkaz:
https://doaj.org/article/a3020b191ee64b2ca284057f3d39c2de
Publikováno v:
Sensors, Vol 22, Iss 19, p 7371 (2022)
This paper proposes a deep learning based object detection method to locate a distant region in an image in real-time. It concentrates on distant objects from a vehicular front camcorder perspective, trying to solve one of the common problems in Adva
Externí odkaz:
https://doaj.org/article/27bb801813274e6fb1c5c36ec23cd178
Publikováno v:
Remote Sensing, Vol 14, Iss 4, p 833 (2022)
To overcome the limitations of standard datasets with data at a wide-variety of scales and captured in the various conditions necessary to train neural networks to yield efficient results in ADAS applications, this paper presents a self-built open-to
Externí odkaz:
https://doaj.org/article/4aa0332306a347a9a663bbd86966f087
Publikováno v:
Sensors, Vol 21, Iss 16, p 5319 (2021)
A method of direction-of-arrival (DoA) estimation for FMCW (Frequency Modulated Continuous Wave) radar is presented. In addition to MUSIC, which is the popular high-resolution DoA estimation algorithm, deep learning has recently emerged as a very pro
Externí odkaz:
https://doaj.org/article/b1021dad82964b52a65b6acd723be5c8