Zobrazeno 1 - 10
of 39
pro vyhledávání: '"Bence Budavari"'
Publikováno v:
IEEE Access, Vol 8, Pp 191997-192008 (2020)
Recognizing normal and anomalous events in long and complex videos with multiple sub-activities has received considerable attention in recent years. This task is more challenging than traditional action recognition in short and relatively homogeneous
Externí odkaz:
https://doaj.org/article/31e6d576e4e34a47af03ca5b8cb27130
Autor:
Chiman Kwan, Bence Budavari
Publikováno v:
Remote Sensing, Vol 12, Iss 24, p 4024 (2020)
The detection of small moving objects in long-range infrared videos is challenging due to background clutter, air turbulence, and small target size. In this paper, we summarize the investigation of efficient ways to enhance the performance of small t
Externí odkaz:
https://doaj.org/article/469ca1896e894ab2be982769ced7cb5a
Autor:
Bulent Ayhan, Chiman Kwan, Bence Budavari, Liyun Kwan, Yan Lu, Daniel Perez, Jiang Li, Dimitrios Skarlatos, Marinos Vlachos
Publikováno v:
Remote Sensing, Vol 12, Iss 15, p 2502 (2020)
Land cover classification with the focus on chlorophyll-rich vegetation detection plays an important role in urban growth monitoring and planning, autonomous navigation, drone mapping, biodiversity conservation, etc. Conventional approaches usually a
Externí odkaz:
https://doaj.org/article/3df07f8bcd7f4597a8f0cf60132b12a2
Autor:
Chiman Kwan, Bulent Ayhan, Bence Budavari, Yan Lu, Daniel Perez, Jiang Li, Sergio Bernabe, Antonio Plaza
Publikováno v:
Remote Sensing, Vol 12, Iss 12, p 2000 (2020)
There is an emerging interest in using hyperspectral data for land cover classification. The motivation behind using hyperspectral data is the notion that increasing the number of narrowband spectral channels would provide richer spectral information
Externí odkaz:
https://doaj.org/article/1ca395bd882d485ea2a5bed9fb98a410
Publikováno v:
Computers, Vol 8, Iss 2, p 32 (2019)
Since lossless compression can only achieve two to four times data compression, it may not be efficient to deploy lossless compression in bandwidth constrained applications. Instead, it would be more economical to adopt perceptually lossless compress
Externí odkaz:
https://doaj.org/article/dc6a4382bf2d4869a19de83ff1af512f
Publikováno v:
Remote Sensing, Vol 10, Iss 9, p 1416 (2018)
High resolution (HR) hyperspectral (HS) images have found widespread applications in terrestrial remote sensing applications, including vegetation monitoring, military surveillance and reconnaissance, fire damage assessment, and many others. They als
Externí odkaz:
https://doaj.org/article/f1697bf6d10141c8bec6db68cce88aba
Publikováno v:
Remote Sensing, Vol 10, Iss 4, p 520 (2018)
We present a new, simple, and efficient approach to fusing MODIS and Landsat images. It is well known that MODIS images have high temporal resolution and low spatial resolution, whereas Landsat images are just the opposite. Similar to earlier approac
Externí odkaz:
https://doaj.org/article/efe3d2d3ef174a199148f55088985252
Autor:
Bence Budavari, Chiman Kwan
Publikováno v:
Signal, Image and Video Processing. 16:93-101
Since targets are small in long-range infrared (IR) videos, it is challenging to accurately detect targets in those videos. In this paper, we propose a high-performance approach to detecting small targets in long-range and low-quality infrared videos
Publikováno v:
Signal & Image Processing : An International Journal. 12:33-45
Long range infrared videos such as the Defense Systems Information Analysis Center (DSIAC) videos usually do not have high resolution. In recent years, there are significant advancement in video super-resolution algorithms. Here, we summarize our stu
Publikováno v:
Signal & Image Processing : An International Journal. 11:25-41
In CFA 2.0, there are white pixels in a color filter array (CFA) that has proven to help the demosaicing performance for images collected in low light conditions. Here, we evaluate the performance of demosaicing for images collected in low light cond