![](images/graphics/blank.gif)
Maximum likelihood detection
-
Ebook "Machine learning in computer vision" includes content: Introduction, probabilistic classifiers, generalization bounds, semi supervised learning, maximum likelihood minimum entropy hmm, margin distribution optimization, learning the structure of bayesian network classifiers, office activity recognition, multimodal event detection, facial expression recognition, bayesian network classifiers for face detection.
249p
haojiubujain07
20-09-2023
4
3
Download
-
Population genetics and association studies usually rely on a set of known variable sites that are then genotyped in subsequent samples, because it is easier to genotype than to discover the variation. This is also true for structural variation detected from sequence data.
13p
vikentucky2711
26-11-2020
22
2
Download
-
Targeted next-generation sequencing (NGS) has been widely used as a cost-effective way to identify the genetic basis of human disorders. Copy number variations (CNVs) contribute significantly to human genomic variability, some of which can lead to disease. However, effective detection of CNVs from targeted capture sequencing data remains challenging.
9p
vioklahoma2711
19-11-2020
8
0
Download
-
The detection of weak signals and selection of single particles from low-contrast micrographs of frozen hydrated biomolecules by cryo-electron microscopy (cryo-EM) represents a major practical bottleneck in cryo-EM data analysis.
17p
vicoachella2711
27-10-2020
24
0
Download
-
In this paper, a new Space-Time Block Coded Spatial Modulation (SM) scheme based on the Golden Code, called the In this paper, we evaluate the symbol error performance of an extended Index Modulation for Orthogonal Frequency Division Multiplexing (IM-OFDM), namely repeated index modulation-OFDM with coordinated interleaving (abbreviated as ReCI), over the Nakagami-m fading channel.
8p
vimariecurie2711
30-07-2019
22
1
Download
-
Given the new unusual and usual event models, both adapted from the general usual event model, the HMM topology is changed with one more state. Hence the cur- rent HMM has 2 states, one representing the usual events and one representing the first detected unusual event. The Viterbi algorithm is then used to find the best possible state sequence which could have emitted the observation sequence, according to the maximum likelihood (ML) cri- terion (Figure 2, step 3). Transition points, which define new segments, are detected using the current HMM topol- ogy and parameters.
10p
nhacsihuytuan
06-04-2013
59
3
Download
-
Signal detection in AWGN channels Minimum distance detector. Maximum likelihood. Average probability of symbol error. Union bound on error probability. Upper bound on error probability based on the minimum distance.ISI in the detection process due to the filtering effects of the system Overall equivalent system transfer function
30p
doanhung_dtvtk10
24-03-2013
66
6
Download
-
Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Efficient Near Maximum-Likelihood Detection for Underdetermined MIMO Antenna Systems Using a Geometrical Approach
13p
sting10
24-02-2012
43
4
Download
CHỦ ĐỀ BẠN MUỐN TÌM
![](images/graphics/blank.gif)