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Supermediastinoscopies: A Step Forward in Lung Cancer Staging
2007
Journal of Thoracic Oncology
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The Union Internationale Contre le Cancer recommends the use of the certainty (C) factor, which is an optional descriptor of the tumor, node, metastasis (TNM) classification that reflects the validity ...
Certainty (C) Factor and Its Applicability
Factor Description of Staging Methods Applicability
C1 Evidence from standard diagnostic means (e.g., inspection, palpation, and standard radiography, intraluminal ...
doi:10.1097/01.jto.0000263721.15062.18
fatcat:yultlkh7m5g7dexp7ubfneoo5u
A Vision-Based Method Utilizing Deep Convolutional Neural Networks for Fruit Variety Classification in Uncertainty Conditions of Retail Sales
2019
Applied Sciences
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The use of the certainty factor associated with prediction results from the original images and cropped ROIs is the main contribution of this paper. ...
Consequently, the method returns the predicted class membership with the Certainty Factor (CF). ...
The authors of [5] also used the nearest-neighbor classifier for fruit classification, but focused on the depth channel of RGBD (Red, Green, Blue, Depth) images. ...
doi:10.3390/app9193971
fatcat:qp4hcnr5q5brrhqilut3cyw6bq
Multi-sensor terrain classification for safe spacecraft landing
2004
IEEE Transactions on Aerospace and Electronic Systems
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A novel multi-sensor information fusion methodology for intelligent terrain classification is presented. ...
The focus of this research is to analyze safety characteristics of the terrain using imagery data obtained by on-board sensors during spacecraft descent. ...
An additional situation we address is when a high certainty factor is not provided by any of the sensors. ...
doi:10.1109/taes.2004.1386868
fatcat:klh6v5dftjfa7nb3ui5jemx2gy
Persistent Confusion on the Clinical and Pathologic Nodal Staging in Lung Cancer
2010
Journal of Thoracic Oncology
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The Certainty Factor 4 offers the possibility to code in a different way those nodes considered involved by imaging methods and by pathologic confirmation in the clinical phase of the tumor classification ...
category is always assumed on the basis of the clinical classification, with a Certainty factor of C1 or C2. ...
surgery trial, I was pleased to see the preliminary results of this study published in the Journal of Thoracic Oncology, 1 with the positive aspects of the trial emphasized in an accompanying editorial by ...
doi:10.1097/jto.0b013e3181ccbaa9
fatcat:qve5wv3i6nbdbluzuv7vn3vy7a
Scope Loss for Imbalanced Classification and RL Exploration
[article]
2023
arXiv
pre-print
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We demonstrate equivalence between the reinforcement learning problem and the supervised classification problem. ...
From our analysis of the aforementioned problems we derive a novel loss function for reinforcement learning and supervised classification. ...
The classification environment can be framed as a one-step episodic MDP, in which each new image is the start of a new episode, with a single action to be immediately followed by a reward and a terminal ...
arXiv:2308.04024v1
fatcat:wwlva3yeo5hoxlhb5kd4yknluu
Diffraction imaging of single particles and biomolecules
2003
Journal of Structural Biology
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A three-dimensional data set can be assembled from such images when many copies of the molecule are exposed to the beam one by one in random orientations. ...
The results can also be used to provide criteria for improvements in other image classification procedures, e.g., those used in electron tomography or diffraction. ...
This work was supported by the Swedish Research Councils STINT and VR. ...
doi:10.1016/j.jsb.2003.09.025
pmid:14643224
fatcat:e6e27x277zhldgmk264l6x2t3e
Analog In-Memory Computing with Uncertainty Quantification for Efficient Edge-based Medical Imaging Segmentation
[article]
2024
arXiv
pre-print
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This work investigates the role of the emerging Analog In-memory computing (AIMC) paradigm in enabling Medical AI analysis and improving the certainty of these models at the edge. ...
Additionally, the paper emphasizes IMC's effective data pipelining, reducing latency and increasing throughput as well as the exploitation of inherent noise within AIMC, strategically harnessed to augment model certainty ...
A.3 EXTENDED CERTAINTY ANALYSIS Figure 3 provides an overall certainty analysis of U-Net++ and Swin U-Net when trained with hardware training versus digital training. ...
arXiv:2403.08796v1
fatcat:su4s6r2hqrgkniwu3rzhmiohbu
A weighted fuzzy classifier and its application to image processing tasks
2007
Fuzzy sets and systems (Print)
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Many image processing applications involve a pattern classification stage. ...
The antecedent part of fuzzy if-then rules are specified by partitioning each attributes into fuzzy sets while the consequent class and the degree of certainty are determined from the compatibility and ...
Weighted fuzzy classification In this paper we extend the principle of fuzzy classification to accommodate weighted training patterns. ...
doi:10.1016/j.fss.2006.10.011
fatcat:tcqekig6pzhjjjzwdvytrcy35q
Measuring Classification Decision Certainty and Doubt
[article]
2023
arXiv
pre-print
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2023 pre-print arXiv:2303.14568v1 fatcat:esq736zbbzfv7pbrkcfgrss3di
(multi-)classification decision machine learning problems. ...
Herein, we propose intuitive scores, which we call certainty and doubt, that can be used in both a Bayesian and frequentist framework to assess and compare the quality and uncertainty of predictions in ...
However, in safety-constrained decision-making, it is crucial to estimate and factor in the level of certainty and doubt associated with each classification decision [3] . ...
arXiv:2303.14568v2
fatcat:t7irbvixbrbltopsgbmg4mgire
Multi-Class Pixel Certainty Active Learning Model for Classification of Land Cover Classes Using Hyperspectral Imagery
2022
Electronics
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This paper extends that work into the novel pixel-certainty activity learning (PCAL) based on the information about textural patterns obtained from the extended differential pattern (EDP). ...
Previously, we focused on the extraction of clear textural pattern information by using the extended differential pattern-based relevance vector machine (EDP-AL). ...
Extended differential pattern (EDP); 3. Pixel-certainty active learning (PCAL). Low-quality images that contain noise have an impact on the depth information. ...
doi:10.3390/electronics11172799
fatcat:xo2rcao7izbh5btm3k5kl3dgii
Acute Ischemic Cerebrovascular Syndrome: Diagnostic Criteria
2003
Stroke
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Diagnostic criteria for AICS incorporate prior classification systems and currently available information provided by neuroimaging and laboratory data to define 4 categories ranging from "definite AICS ...
" to "not AICS," which define the degree of diagnostic certainty. ...
Most importantly, it incorporates the evidence-based diagnostic certainty offered by neuroimaging techniques as used in the new MS classification scheme. ...
doi:10.1161/01.str.0000098902.69855.a9
pmid:14605325
fatcat:esvgx23mgfbg5f2pnlpgygb4au
Infrared Thermography Based Defects Testing of Solar Photovoltaic Panel with Fuzzy Rule-Based Evaluation
2020
Energies
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In this work, the fuzzy rule-based classification system is proposed to automate the classification process. ...
The real-time experimental testing was carried out using FLIR T420bx® thermal imager and results have been provided to validate the proposed method. ...
factors and real-time operating conditions in image measurement. ...
doi:10.3390/en13061343
fatcat:4ypfp4q2evdtjewxesnzlg4gki
MECnIT 2020 Table of Contents
2020
2020 3rd International Conference on Mechanical, Electronics, Computer, and Industrial Technology (MECnIT)
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Factor Methods to Determine Skills in Generation Networks Study of UAV Application in Wireless Sensor Expert System for Diagnosing Dental and Oral Diseases with Certainty Design and Implementation of ...
Review of Solar Photovoltaic Android-Based Applications for Analysis Optimization K-Nearest Neighbor Algorithm with Certainty Factor in Determining Student Career 188 202 332 207 327 321 317 198 311 194 ...
doi:10.1109/mecnit48290.2020.9166683
fatcat:fcqdgdv635hq5avguytovgj4jy
K NN-CF Approach: Incorporating Certainty Factor to k NN Classification
2010
The IEEE intelligent informatics bulletin
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This paper incorporates certainty factor (CF) measure to kNN classification, called kNN-CF classification, so as to deal with the above issue. ...
This leads to that an existing kNN classification algorithm can easily be extended to the setting of skewed class distribution. ...
ACKNOWLEDGMENT I am grateful for both the suggestions and the experiments carried out by my ex-student, Mr Manlong Zhu. ...
dblp:journals/cib/Zhang10
fatcat:ufs65vnumbba3gdzhwc24zyhpy
Learning Semantically Meaningful Embeddings Using Linear Constraints
2019
Computer Vision and Pattern Recognition
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As shown in Table 1 , our learning approach gives a clear better classification accuracy than both AE or VAE on a held-out test set of 10k images. ...
Linear High Certainty Low Certainty a) b) c) d) e) f) g) h) i) High Certainty (Row 1) Query Probability Distributions a) [0.9, 0, 0, 0, 0, 0, 0.1, 0, 0, 0] b) [0, 1, 0, 0, 0, 0, 0, 0, 0, 0] c) [0, 0, 0.6 ...
dblp:conf/cvpr/LinYBC19
fatcat:lnqk7zrypjhvdl27lj65cislne
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