Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Mandlenkosi Victor Gwetu"'
Publikováno v:
Geocarto International, Vol 38, Iss 1 (2023)
Modern earth observation sensors have revolutionized the remote sensing community by improving remote sensing image quality. However, Pixel-based image analysis methods have challenges in handling very high-resolution (VHR) imagery. Geographic Based
Externí odkaz:
https://doaj.org/article/bc07a390f8f14e8393abe2895167b174
Publikováno v:
South African Computer Journal, Vol 0, Iss 55 (2014)
Although computerized retinal image blood vessel segmentation has been extensively researched, there is still room for improvement in the quality of the segmented images. Since retinal image analysis is still widely used in the diagnosis of diabetic
Externí odkaz:
https://doaj.org/article/760779bdc31b407485331c5db481bb36
Autor:
Mandlenkosi Victor Gwetu
Publikováno v:
Machine Learning for Networking ISBN: 9783030708658
MLN
MLN
Dynamic Time Warping (DTW) is a tried and tested online signature verification technique that still finds relevance in modern studies. However, DTW operates in a writer-dependent manner and its algorithm outputs unbounded distance values. The introdu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d254cff3e488648b434af789b3e8d83a
https://doi.org/10.1007/978-3-030-70866-5_9
https://doi.org/10.1007/978-3-030-70866-5_9
Contrast Enhancement in Deep Convolutional Neural Networks for Segmentation of Retinal Blood Vessels
Publikováno v:
Recent Challenges in Intelligent Information and Database Systems ISBN: 9789811616846
ACIIDS (Companion)
ACIIDS (Companion)
The segmentation of blood vessels from the retinal fundus image is known to be complicated. This difficulty results from visual complexities associated with retinal fundus images such as low contrast, uneven illumination, and noise. These visual comp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3d60b0229aa3a7549519124cf0359384
https://doi.org/10.1007/978-981-16-1685-3_23
https://doi.org/10.1007/978-981-16-1685-3_23
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030770037
MCPR
MCPR
This paper presents experimental results obtained from using weakly tuned deep learning models as feature extraction mechanisms which are used to train regressor models for skeletal age estimation from hand radiographs of the RSNA Bone Age dataset. B
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1c165202d423ea10193fe39bec42ac89
https://doi.org/10.1007/978-3-030-77004-4_17
https://doi.org/10.1007/978-3-030-77004-4_17
Publikováno v:
Mining Intelligence and Knowledge Exploration ISBN: 9783030661861
MIKE
MIKE
This paper presents experimental results obtained from using weakly tuned deep learning models for skeletal age estimation from hand radiographs. By leveraging transfer learning, deep learning models were initialised with the ImageNet dataset weights
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0f1ce27cc09fb228c77ed87e4b5eecfc
https://doi.org/10.1007/978-3-030-66187-8_16
https://doi.org/10.1007/978-3-030-66187-8_16
Publikováno v:
Machine Learning for Networking ISBN: 9783030457778
MLN
Lecture Notes in Computer Science
2nd International Conference on Machine Learning for Networking (MLN)
2nd International Conference on Machine Learning for Networking (MLN), Dec 2019, Paris, France. pp.255-272, ⟨10.1007/978-3-030-45778-5_17⟩
MLN
Lecture Notes in Computer Science
2nd International Conference on Machine Learning for Networking (MLN)
2nd International Conference on Machine Learning for Networking (MLN), Dec 2019, Paris, France. pp.255-272, ⟨10.1007/978-3-030-45778-5_17⟩
International audience; Although Random Forests (RFs) are an effective and scalable ensemble machine learning approach, they are highly dependent on the discriminative ability of the available individual features. Since most data mining problems occu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b47d3839b723a064a10d713470317102
https://doi.org/10.1007/978-3-030-45778-5_17
https://doi.org/10.1007/978-3-030-45778-5_17
Publikováno v:
Computational Collective Intelligence ISBN: 9783030630065
ICCCI
ICCCI
Melanoma is one of the most dangerous forms of skin cancer with an apace increase in death rates each year. One major problem in Artificial Intelligence and Machine Learning is the issue of racial disparities. This leads to myriad problems in associa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::37bb9d37e6bd3cb3c9152374f6be281a
https://doi.org/10.1007/978-3-030-63007-2_41
https://doi.org/10.1007/978-3-030-63007-2_41
Publikováno v:
Computational Collective Intelligence ISBN: 9783030630065
ICCCI
ICCCI
The quest for automated diagnosis of diabetic retinopathy continues due to increasing prevalence coupled with scarcity of skilled medical experts, especially in the third world. Due to the significant role that retinal image analysis plays in such di
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9ef7e4869d836a879edd951170d22a1f
https://doi.org/10.1007/978-3-030-63007-2_40
https://doi.org/10.1007/978-3-030-63007-2_40
Publikováno v:
Advances in Computational Collective Intelligence ISBN: 9783030631185
ICCCI (CCIS Volume)
ICCCI (CCIS Volume)
Melanoma is one of the most aggressive types of skin cancer as it rapidly spreads to various areas of the body. With the increase and fatal nature of melanoma, it is of utmost importance to establish computer assisted diagnostic support systems to ai
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8c2935f4a19d11b36b5a54e5f838feeb
https://doi.org/10.1007/978-3-030-63119-2_24
https://doi.org/10.1007/978-3-030-63119-2_24