Results 141 to 150 of about 9,834 (275)
Unsupervised Segmentation Method for Brain MRI Based on Fuzzy Techniques
مجلة النهرين للعلوم الهندسية, 2010 In the present research a novel spatially weighted Fuzzy C-Means (FCM) clustering algorithm for image thresholding is presented. The segmentation technique is for magnetic resonance (MR) images of the brain based on fuzzy algorithms for learning vector ...
Nasser N. Khamiss
doaj
DrLS: Distortion‐Resistant Lossless Steganography via Colour Depth Interpolation
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT The lossless data steganography is to hide a certain amount of information into a container image. Previous lossless steganography methods fail to strike a balance between capacity, imperceptibility, accuracy, and robustness, commonly vulnerable to distortion on container images.
Youmin Xu +3 more
wiley +1 more source
A Quantised Push‐Sum Distributed Adaptive Momentum Algorithm for Optimisation Over Directed Networks
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT In this paper, we investigate a distributed constrained optimisation problem over directed networks. The agents in the networks conduct local computations and communications, endeavouring to collaboratively minimise the aggregation of all locally known convex cost functions subject to a global constraint set.
Qingguo Lü +6 more
wiley +1 more source
Learning Vector Quantization with Training Count (LVQTC)
Neural Networks, 1997 Kohonen's learning vector quantization (LVQ) is modified by attributing training counters to each neuron, which record its training statistics. During training, this allows for dynamic self-allocation of the neurons to classes. In the classification stage training counters provide an estimate of the reliability of classification of the single neurons ...
openaire +3 more sources
FMTNet: A Fourier‐Mamba–Transformer Enhanced Network for Medical Image Segmentation
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Models based on U‐shaped networks have achieved widespread success in the field of medical image segmentation, but their performance is generally limited by structural bottlenecks in the network. At this stage, feature maps experience a sharp decline in spatial resolution due to continuous downsampling, resulting in significant loss of ...
Shaoqiang Wang +7 more
wiley +1 more source
Integrative Zoology, EarlyView.Research on mosquito feeding preferences and the malaria parasites they transmit is essential for understanding the interactions between hosts, vectors, and parasites. In this study, vertebrate hosts were identified in 72 mosquitoes. Most blood meals (58.7%) came from birds, representing 25 species, while 40.0% came from mammals (13 species), and 1.3 ...
Qin Zhang +8 more
wiley +1 more source
Using Of Learning Vector Quantization Network for Pan Evaporation Estimation
Tikrit Journal of Engineering Sciences, 2013 A modern technique is presented to study the evaporation process which is considered as an important component of the hydrological cycle. The Pan Evaporation depth is estimated depending upon four metrological factors viz. (temperature, relative humidity,
Kamil7 A. Abdulmohsen, Iftikar A. Al Ani
doaj
ANALISIS SENTIMEN MENGGUNAKAN METODE LEARNING VECTOR QUANTIZATION [PDF]
, 2017 Media sosial sebagai media komunikasi untuk menghubungkan semua orang menjadi mudah diterima oleh masyarakat seiring dengan perkembangan teknologi informasi.
M. INDRA HALIM ARSYA DWI AKBARI
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A Real‐Time Multi‐Scale Neural Representation for Complex Surface Reflectance
Computer Graphics Forum, EarlyView.Abstract Recent machine learning methods have significantly advanced the state of the art in the classic problem of representing surface appearance over angle, space, and scale. The models tend, however, to be relatively heavy compared to traditional fixed‐function representations, making real‐time application challenging.
Heikki Timonen +2 more
wiley +1 more source
Differential Privacy for Learning Vector Quantization
, 2017 Brinkrolf J, Berger K, Hammer B. Differential Privacy for Learning Vector Quantization.
Hammer, Barbara ; https://orcid.org/ +2 more
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