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Journal articles on the topic 'Landmark Selection'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Wang, Huaxia, Yongmei Cheng, Nan Liu, Shun Yao, Juanjuan Ma, and Huibin Wang. "A Fast Selection Method of Landmarks for Terrain Matching Navigation." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 38, no. 5 (2020): 959–64. http://dx.doi.org/10.1051/jnwpu/20203850959.

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Under fixed imaging conditions, the landmark selection method based feature traversal analysis has high computational complexity. The hierarchical statistical significance detection method uses global statistical information for feature analysis to overcome the computational complexity problem caused by feature traversal analysis. The frequency domain de-correlation method can remove repeat mode in the image by adaptive Gaussian filtering on the amplitude-frequency characteristics. In this paper, combined the hierarchical statistical saliency detection method with the frequency domain de-corre

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Zenou, Emmanuel, and Manuel Samuelides. "Galois Lattice Theory for Probabilistic Visual Landmarks." JUCS - Journal of Universal Computer Science 10, no. (8) (2004): 1014–33. https://doi.org/10.3217/jucs-010-08-1014.

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This paper presents an original application of the Galois lattice theory, the visual landmark selection for topological localization of an autonomous mobile robot, equipped with a color camera. First, visual landmarks have to be selected in order to characterize a structural environment. Second, such landmarks have to be detected and updated for localization. These landmarks are combinations of attributes, and the selection process is done through a Galois lattice. This paper exposes the landmark selection process and focuses on probabilistic landmarks, which give the robot thorough informatio

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Zhu, Litao, Milan Konečný, Jie Shen, Zdeněk Stachoň, and Hana Švedová. "The Influence of Spatial Familiarity on Landmark Salience Sensibility Based on Eye Tracking." Abstracts of the ICA 1 (July 15, 2019): 1–2. http://dx.doi.org/10.5194/ica-abs-1-438-2019.

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<p><strong>Abstract.</strong> Landmarks play an important role in navigation especially when people in the familiar and unfamiliar environment. These landmarks are usually used for expressing their spatial knowledge. This prior knowledge is related to the spatial familiarity that the spatial knowledge is acquired by individuals as a function of their experience in the environment (Gale et al., 1990). Individuals prefers to take into highly account their familiar route within the environment. Furthermore, the route descriptions include the differed types of landmarks in famili

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Wu, Chi-Fang, Natasha S. Savage, and Daniel J. Lew. "Interaction between bud-site selection and polarity-establishment machineries in budding yeast." Philosophical Transactions of the Royal Society B: Biological Sciences 368, no. 1629 (2013): 20130006. http://dx.doi.org/10.1098/rstb.2013.0006.

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Saccharomyces cerevisiae yeast cells polarize in order to form a single bud in each cell cycle. Distinct patterns of bud-site selection are observed in haploid and diploid cells. Genetic approaches have identified the molecular machinery responsible for positioning the bud site: during bud formation, specific locations are marked with immobile landmark proteins. In the next cell cycle, landmarks act through the Ras-family GTPase Rsr1 to promote local activation of the conserved Rho-family GTPase, Cdc42. Additional Cdc42 accumulates by positive feedback, creating a concentrated patch of GTP-Cdc

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Liang, Dong, Chen Qiao, and Zongben Xu. "Enhancing Both Efficiency and Representational Capability of Isomap by Extensive Landmark Selection." Mathematical Problems in Engineering 2015 (2015): 1–18. http://dx.doi.org/10.1155/2015/241436.

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The problems of improving computational efficiency and extending representational capability are the two hottest topics in approaches of global manifold learning. In this paper, a new method called extensive landmark Isomap (EL-Isomap) is presented, addressing both topics simultaneously. On one hand, originated from landmark Isomap (L-Isomap), which is known for its high computational efficiency property, EL-Isomap also possesses high computational efficiency through utilizing a small set of landmarks to embed all data points. On the other hand, EL-Isomap significantly extends the representati

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Sala, P., R. Sim, A. Shokoufandeh, and S. Dickinson. "Landmark Selection for Vision-Based Navigation." IEEE Transactions on Robotics 22, no. 2 (2006): 334–49. http://dx.doi.org/10.1109/tro.2005.861480.

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Lerner, R., E. Rivlin, and I. Shimshoni. "Landmark Selection for Task-Oriented Navigation." IEEE Transactions on Robotics 23, no. 3 (2007): 494–505. http://dx.doi.org/10.1109/tro.2007.895070.

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Deng, Xiaotie, Evangelos Milios, and Andy Mirzaian. "Landmark selection strategies for path execution." Robotics and Autonomous Systems 17, no. 3 (1996): 171–85. http://dx.doi.org/10.1016/0921-8890(95)00042-9.

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9

Meunier, Pierre. "Use of Body Shape Information in Clothing Size Selection." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 44, no. 38 (2000): 715–18. http://dx.doi.org/10.1177/154193120004403808.

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To investigate the role of body shape information on clothing size selection, a sample of 143 males were measured and sized using a computerized digital-image based measurement system. Clothing sizes were initially determined by the system using traditional criteria for the long sleeve shirt, jacket and trousers of a military dress uniform. The best-fitting size was determined by trial and error based on subjective feedback and expert judgement, provided by clothing and sizing technicians. Discriminant function analysis was used to determine sizing rules for each garment, based on different se

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Clayman, Carly L., Alakesh Mani, Suraj Bondugula, and Satish M. Srinivasan. "Tissue Classification Using Landmark and Non-Landmark Gene Sets for Feature Selection." Procedia Computer Science 185 (2021): 256–63. http://dx.doi.org/10.1016/j.procs.2021.05.027.

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Copson, Bridget, Sudanthi Wijewickrema, Christopher Slinger, Daniel Youssef, Jean-Marc Gerard, and Stephen O’Leary. "Definition of a coordinate system for multi-modal images of the temporal bone and inner ear." PLOS ONE 19, no. 10 (2024): e0294828. http://dx.doi.org/10.1371/journal.pone.0294828.

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Purpose The position and orientation of the head is maintained to be relatively similar during the CT / MR imaging process. However, the position / orientation dissimilarities present in the resulting images between patients, or between different scans of the same patient, do not allow for direct comparison of the images themselves or features / metrics extracted from them. This paper introduces a method of defining a coordinate system which is consistent between patients and modalities (CT and MR) for images of the temporal bone, using easily identifiable landmarks within the semicircular can

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Shi, Hao, Baoqun Yin, Yu Kang, Chao Shao, and Jie Gui. "Robust L-Isomap with a Novel Landmark Selection Method." Mathematical Problems in Engineering 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/3930957.

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Isomap is a widely used nonlinear method for dimensionality reduction. Landmark-Isomap (L-Isomap) has been proposed to improve the scalability of Isomap. In this paper, we focus on two important issues that were not taken into account in L-Isomap, landmark point selection and topological stability. At first, we present a novel landmark point selection method. It first uses a greedy strategy to select some points as landmark candidates and then removes the candidate points that are neighbours of other candidates. The remaining candidate points are the landmark points. The selection method can p

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LEMMENS, N., and K. TUYLS. "STIGMERGIC LANDMARK OPTIMIZATION." Advances in Complex Systems 15, no. 08 (2012): 1150025. http://dx.doi.org/10.1142/s0219525911500251.

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In this paper we present three Swarm Intelligence algorithms which we evaluate on the complex foraging task domain. Each of the algorithms draws inspiration from biologic bee foraging/nest-site selection behavior. The main focus will be on the third algorithm, namely STIGMERGIC LANDMARK FORAGING which is a novel hybrid approach. It combines the high performance of bee-inspired navigation with ant-inspired recruitment. More precisely, navigation is based on Path Integration which results in vectors indicating the distance and direction to a destination. Recruitment only occurs at key locations

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Bürki, Mathias, Cesar Cadena, Igor Gilitschenski, Roland Siegwart, and Juan Nieto. "Appearance‐based landmark selection for visual localization." Journal of Field Robotics 36, no. 6 (2019): 1041–73. http://dx.doi.org/10.1002/rob.21870.

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Sangiru, Sangiru, Maria Immaculata Ririk Winandari, and Etty Retnowati Kridarso. "VISITORS’ PERCEPTION: THE LANDMARKS OF BANTEN LAMA." International Journal on Livable Space 3, no. 2 (2019): 104. http://dx.doi.org/10.25105/livas.v3i2.3776.

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<div class="page" title="Page 1"><div class="section"><div class="layoutArea"><div class="column"><p><span>Banten Lama District, the centre of Banten Sultanate, has several preserved historical buildings and sites. </span><span>One of the historical buildings is Masjid Agung that is considered as Banten Lama Landmark refering to its nickname ‘santri city’. This visual research aimed to identify Banten of 40 visitors of Banten Cultural Festival that randomly chosen. Quantitative analysis using the Osgood scale was used to obtain the landmark prior

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Chi, Junhwa, and Melba Crawford. "Selection of Landmark Points on Nonlinear Manifolds for Spectral Unmixing Using Local Homogeneity." Geoscience and Remote Sensing Letters, IEEE 10, no. 4 (2012): 711–15. http://dx.doi.org/10.1109/lgrs.2012.2219613.

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Endmember extraction and unmixing methods that exploit nonlinearity in hyperspectral data are receiving increased attention, but they have significant challenges. Global feature extraction methods such as isometric feature mapping have significant computational overhead, which is often addressed for the classification problem via landmark-based methods. Because landmark approaches are approximation methods, experimental results are often highly variable. We propose a new robust landmark selection method for the purpose of pixel unmixing that exploits spectral and spatial homogeneity in a local

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Schwendicke, Falk, Akhilanand Chaurasia, Lubaina Arsiwala, et al. "Deep learning for cephalometric landmark detection: systematic review and meta-analysis." Clinical Oral Investigations 25, no. 7 (2021): 4299–309. http://dx.doi.org/10.1007/s00784-021-03990-w.

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Abstract Objectives Deep learning (DL) has been increasingly employed for automated landmark detection, e.g., for cephalometric purposes. We performed a systematic review and meta-analysis to assess the accuracy and underlying evidence for DL for cephalometric landmark detection on 2-D and 3-D radiographs. Methods Diagnostic accuracy studies published in 2015-2020 in Medline/Embase/IEEE/arXiv and employing DL for cephalometric landmark detection were identified and extracted by two independent reviewers. Random-effects meta-analysis, subgroup, and meta-regression were performed, and study qual

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Traverso, Francesca, Stefano Aicardi, Matteo Bozzo, et al. "New Insights into Geometric Morphometry Applied to Fish Scales for Species Identification." Animals 14, no. 7 (2024): 1090. http://dx.doi.org/10.3390/ani14071090.

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The possibility of quick and cheap recognition of a fish species from a single dermal scale would be interesting in a wide range of contexts. The methods of geometric morphometry appear to be quite promising, although wide studies comparing different approaches are lacking. We aimed to apply two methods of geometric morphometry, landmark-based and outline-based, on a dataset of scales from five different teleost species: Danio rerio, Dicentrarchus labrax, Mullus surmuletus, Sardina pilchardus, and Sparus aurata. For the landmark-based method the R library “geomorph” was used. Some issues about

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Chi, Junhwa. "Maximum Simplex Volume based Landmark Selection for Isomap." Korean Journal of Remote Sensing 29, no. 5 (2013): 509–16. http://dx.doi.org/10.7780/kjrs.2013.29.5.6.

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Madsen, Claus B., and Claus S. Andersen. "Optimal landmark selection for triangulation of robot position." Robotics and Autonomous Systems 23, no. 4 (1998): 277–92. http://dx.doi.org/10.1016/s0921-8890(98)00014-1.

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Yi, Chuho, Yongmin Shin, and Jungwon Cho. "Automatic Landmark Selection Using Clustering for Robot SLAM." International Journal of Multimedia and Ubiquitous Engineering 9, no. 1 (2014): 77–88. http://dx.doi.org/10.14257/ijmue.2014.9.1.08.

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22

Xiu, Wenbo, Jiateng Long, Shengying Zhu, and Pingyuan Cui. "Landmark robust selection for asteroid landing visual navigation." Acta Astronautica 214 (January 2024): 665–76. http://dx.doi.org/10.1016/j.actaastro.2023.11.029.

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23

Mao, Li, Delei Zhang, Youming Chen, Tao Zhang, and Xiaoning Song. "Deep aligned feature extraction for collaborative-representation-based face classification with group dictionary selection." International Journal of Advanced Robotic Systems 17, no. 6 (2020): 172988142096757. http://dx.doi.org/10.1177/1729881420967577.

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Face recognition plays an important role in many robotic and human–computer interaction systems. To this end, in recent years, sparse-representation-based classification and its variants have drawn extensive attention in compress sensing and pattern recognition. For image classification, one key to the success of a sparse-representation-based approach is to extract consistent image feature representations for the images of the same subject captured under a wide spectrum of appearance variations, for example, in pose, expression and illumination. These variations can be categorized into two mai

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Rafailidis, D., E. Constantinou, and Y. Manolopoulos. "Landmark selection for spectral clustering based on Weighted PageRank." Future Generation Computer Systems 68 (March 2017): 465–72. http://dx.doi.org/10.1016/j.future.2016.03.006.

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25

Rupic, Ivana, Ivana Čuković-Bagić, Vladimir Ivković, and Tomislav Lauc. "Assessment of facial landmarks for bone asymmetry in geometric morphometric studies: A review." South European Journal of Orthodontics and Dentofacial Research 7, no. 2(S) (2021): 6–16. http://dx.doi.org/10.5937/sejodr7-29735.

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Background Anthropometrical points or landmarks are key for facial shape analysis using geometric morphometrics. In the early 1990s Fred Bookstein created a classification system with landmarks type 1., type 2., type 3. based on anatomical landmark homology. However, thirty years later, a uniform referece index of landmarks that can be used for assessing facial asymmetry still does not exist. The criteria for selecting landmark points are not fully defined, which makes classification of homology and and landmarks prone to arbitrary interpretations. A systematic review of literature indic

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Fang, Hao, Hongyun Guo, Zhangtong Song, Nai Yang, Rui Wang, and Fen Guo. "The Influence of the Relationship Between Landmark Symbol Types, Annotations, and Colors on Search Performance in Mobile Maps Based on Eye Tracking." ISPRS International Journal of Geo-Information 14, no. 3 (2025): 129. https://doi.org/10.3390/ijgi14030129.

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Mobile map landmark symbols are pivotal in conveying spatial semantics and enhancing users’ perception of digital maps. This study employs a three-factor hybrid experimental design to investigate the effects of different landmark symbol types and their color associations with annotations on search performance using eye tracking methods. Utilizing the Tobii X2-60 eye tracker, 40 participants engaged in a visual search task across three symbol types (icons, indexes, and symbols) and two color conditions (consistent and inconsistent). This study also examines the impact of gender on search perfor

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Kavousinejad, Shahab, Asghar Ebadifar, Azita Tehranchi, Farzan Zakermashhadi, and Kazem Dalaie. "Determination of cervical vertebral maturation using machine learning in lateral cephalograms." Journal of Dental Research, Dental Clinics, Dental Prospects 18, no. 4 (2024): 232–41. https://doi.org/10.34172/joddd.41114.

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Background. The accurate timing of growth modification treatments is crucial for optimal results in orthodontics. However, traditional methods for assessing growth status, such as hand-wrist radiographs and subjective interpretation of lateral cephalograms, have limitations. This study aimed to develop a semi-automated approach using machine learning based on cervical vertebral dimensions (CVD) for determining skeletal maturation status. Methods. A dataset comprising 980 lateral cephalograms was collected from the Department of Orthodontics, Shahid Beheshti Dental School in Tehran, Iran. Eight

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Zhai, Guang Fei, Guang Da Su, and Jiong Xin Liu. "Research of Facial Features Extraction Based on Improved ASM." Advanced Materials Research 271-273 (July 2011): 131–36. http://dx.doi.org/10.4028/www.scientific.net/amr.271-273.131.

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Traditional ASM (Active Shape Model) methods usually depend heavily on the initial facial landmark positions located by the face detector. During the fitting process the ASM model may be trapped into local optima instead of the global optima due to the inaccurate initial position selection. In this paper we present that this problem can be solved by incorporating pupil and chin localizations in adjusting the initial landmark positions, together with adaptive step length selection based on two-dimensional gradient characteristic in a multi-scale ASM model. Experiments on a face database consist

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Belabbas, Mohamed-Ali, and Patrick J. Wolfe. "On landmark selection and sampling in high-dimensional data analysis." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 367, no. 1906 (2009): 4295–312. http://dx.doi.org/10.1098/rsta.2009.0161.

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In recent years, the spectral analysis of appropriately defined kernel matrices has emerged as a principled way to extract the low-dimensional structure often prevalent in high-dimensional data. Here, we provide an introduction to spectral methods for linear and nonlinear dimension reduction, emphasizing ways to overcome the computational limitations currently faced by practitioners with massive datasets. In particular, a data subsampling or landmark selection process is often employed to construct a kernel based on partial information, followed by an approximate spectral analysis termed the N

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Qian, Biao, Yang Wang, Richang Hong, Meng Wang, and Ling Shao. "Diversifying Inference Path Selection: Moving-Mobile-Network for Landmark Recognition." IEEE Transactions on Image Processing 30 (2021): 4894–904. http://dx.doi.org/10.1109/tip.2021.3076275.

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Orsenigo, Carlotta. "An improved set covering problem for Isomap supervised landmark selection." Pattern Recognition Letters 49 (November 2014): 131–37. http://dx.doi.org/10.1016/j.patrec.2014.07.007.

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Gerstmayr, Lorenz, Alexandre Bernardino, and José Santos-Victor. "Appearance based landmark selection and reliability evaluation for topological navigation." IFAC Proceedings Volumes 37, no. 8 (2004): 108–13. http://dx.doi.org/10.1016/s1474-6670(17)31959-6.

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Xiao, Ting, Peng Liu, Wei Zhao, and Xianglong Tang. "Iterative landmark selection and subspace alignment for unsupervised domain adaptation." Journal of Electronic Imaging 27, no. 03 (2018): 1. http://dx.doi.org/10.1117/1.jei.27.3.033037.

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Kettunen, Pyry. "Experiment on People’s Selection of Route Landmarks from Different Types of Geospatial Pictures." Abstracts of the ICA 1 (July 15, 2019): 1–2. http://dx.doi.org/10.5194/ica-abs-1-172-2019.

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<p><strong>Abstract.</strong> Different types of geospatial pictures, such as maps and aerial imagery, have varying potential to provide spatial knowledge for the viewers. Our earlier review has assessed different common types of geopictures with regard to their support for acquiring different types of spatial knowledge (Kettunen et al., 2012). The assessment was based on previous literature about geopicture experiments as well as analytical itemization of the information available on the pictures as a function of picture characteristics, namely vantage point, number of visib

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Chen, Yuzhong, Yang Yu, and Guolong Chen. "Shortest distance estimation in large scale graphs." Engineering Computations 31, no. 8 (2014): 1635–47. http://dx.doi.org/10.1108/ec-11-2012-0286.

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Purpose – Shortest distance query between a pair of nodes in a graph is a classical problem with a wide variety of applications. Exact methods for this problem are infeasible for large-scale graphs such as social networks with hundreds of millions of users and links due to their high complexity of time and space. The purpose of this paper is to propose a novel landmark selection strategy which can estimate the shortest distances in large-scale graphs and clarify the efficiency and accuracy of the proposed strategy in comparison with currently used strategies. Design/methodology/approach – Diff

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SHIMODA, Masamichi, and Kimitoshi YAMAZAKI. "2A1-U06 Quality Visual Landmark Selection Based on Distinctiveness and Repeatablity." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2015 (2015): _2A1—U06_1—_2A1—U06_4. http://dx.doi.org/10.1299/jsmermd.2015._2a1-u06_1.

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Wang, Chong, and Hongyi Wu. "Self-configurable border landmark selection in wireless networks: Algorithms and applications." Pervasive and Mobile Computing 6, no. 1 (2010): 128–43. http://dx.doi.org/10.1016/j.pmcj.2009.07.017.

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Zhang, Chunjie, Yifan Zhang, Xiaobin Zhu, et al. "Socio-mobile landmark recognition using local features with adaptive region selection." Neurocomputing 172 (January 2016): 100–113. http://dx.doi.org/10.1016/j.neucom.2014.10.105.

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Rouhi, Alireza, Asgarali Bouyer, Bahman Arasteh, and Xiaoyang Liu. "Two-pronged feature reduction in spectral clustering with optimized landmark selection." Applied Soft Computing 161 (August 2024): 111775. http://dx.doi.org/10.1016/j.asoc.2024.111775.

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Lee, Sangho, Hayun Lee, and Dongkun Shin. "Proxyformer: Nyström-Based Linear Transformer with Trainable Proxy Tokens." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 12 (2024): 13418–26. http://dx.doi.org/10.1609/aaai.v38i12.29244.

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Transformer-based models have demonstrated remarkable performance in various domains, including natural language processing, image processing and generative modeling. The most significant contributor to the successful performance of Transformer models is the self-attention mechanism, which allows for a comprehensive understanding of the interactions between tokens in the input sequence. However, there is a well-known scalability issue, the quadratic dependency (i.e. O(n^2)) of self-attention operations on the input sequence length n, making the handling of lengthy sequences challenging. To add

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Suweko, Sangiru Kasmo, Maria Immaculata Ririk winandari, and Etty Retnowati Kridarso. "BANTEN LAMA LANDMARK BASED ON VISITORS PERCEPTION." International Journal on Livable Space 3, no. 2 (2018): 104. http://dx.doi.org/10.25105/livas.v3i2.3168.

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<p><br />Old Banten Region is an area that is famous for trading at its time. Currently, related to the past glory this place turn into a religious tourist destination .There are still many relics of ancient buildings which show the image of the past glory as well as the element of the city image in Old Banten Region . This study has aim to explore the image of the city of Banten Lama based on visitors' visual perception. The research method uses visual perception method with a rating rating of 14 Landmarks (tetenger) selected based on case selection. Respondents consisted of 40 vi

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Xu, Chao, Xiangyu Huang, Maodeng Li, and Dayi Wang. "Landmark database selection for vision-aided inertial navigation in planetary landing missions." Aerospace Science and Technology 118 (November 2021): 107040. http://dx.doi.org/10.1016/j.ast.2021.107040.

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Li, Zhiqiang, Jingwen Niu, Xiao-Yuan Jing, Wangyang Yu, and Chao Qi. "Cross-Project Defect Prediction via Landmark Selection-Based Kernelized Discriminant Subspace Alignment." IEEE Transactions on Reliability 70, no. 3 (2021): 996–1013. http://dx.doi.org/10.1109/tr.2021.3074660.

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Mkrtchyan, Katya, Anirban Chakraborty, and Amit K. Roy-Chowdhury. "Optimal Landmark Selection for Registration of 4D Confocal Image Stacks in Arabidopsis." IEEE/ACM Transactions on Computational Biology and Bioinformatics 14, no. 2 (2017): 457–67. http://dx.doi.org/10.1109/tcbb.2016.2527655.

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Rashmi, Manazhy, and Praveen Sankaran. "Optimal Landmark Point Selection Using Clustering for Manifold Modeling and Data Classification." Journal of Classification 36, no. 1 (2019): 94–112. http://dx.doi.org/10.1007/s00357-018-9285-7.

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Bao, Zhaoyao, Ziyu Zhang, and Chi Xie. "Landmark selection and path planning for unmanned vehicles with position error corrections." Transportation Research Part C: Emerging Technologies 153 (August 2023): 104186. http://dx.doi.org/10.1016/j.trc.2023.104186.

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Dobai, Adrienn, Zsolt Markella, Miklós Mezei, and Tamás Vizkelety. "Statistics-based Landmark Selection Model for Conebeam CT-derived Three-Dimensional Cephalometry." Acta Polytechnica Hungarica 15, no. 6 (2018): 235–49. http://dx.doi.org/10.12700/aph.15.6.2018.6.12.

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Wu, Xinxing, and Qiang Cheng. "Fractal Autoencoders for Feature Selection." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 12 (2021): 10370–78. http://dx.doi.org/10.1609/aaai.v35i12.17242.

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Feature selection reduces the dimensionality of data by identifying a subset of the most informative features. In this paper, we propose an innovative framework for unsupervised feature selection, called fractal autoencoders (FAE). It trains a neural network to pinpoint informative features for global exploring of representability and for local excavating of diversity. Architecturally, FAE extends autoencoders by adding a one-to-one scoring layer and a small sub-neural network for feature selection in an unsupervised fashion. With such a concise architecture, FAE achieves state-of-the-art perf

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Pattnaik, Tapaswini, and Priyadarshi Kanungo. "Adaptive Window Selection for Non-uniform Lighting Image Thresholding." ELCVIA Electronic Letters on Computer Vision and Image Analysis 20, no. 1 (2021): 42–54. http://dx.doi.org/10.5565/rev/elcvia.1301.

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Selection of appropriate size of windows or subimages is the most important step for thresholding images with non-uniform lighting. In this paper, a novel criteria function is developed to partition images into different size of sub images appropriate for thresholding. After the partitioning, each subimage is segmented by Otsu’s thresholding approaches. The performance of the proposed method is validated on benchmark test images with different degree of uneven lighting. Based on the qualitative and quantitative measures, the proposed method is fully automatic, fast and efficient in comparison

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Alawadi, Zeinab, Uma Phatak, Chung-Yuan Hu, et al. "Comparative effectiveness of primary tumor resection in metastatic colon cancer: An instrumental variable analysis." Journal of Clinical Oncology 33, no. 3_suppl (2015): 674. http://dx.doi.org/10.1200/jco.2015.33.3_suppl.674.

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Abstract:

674 Background: Although the safety of chemotherapy without primary tumor resection (PTR) has been established, questions remain regarding potential survival benefit with PTR. The purpose of this study was to compare mortality with and without PTR among patients with unresectable metastatic colon cancer using nationwide hospital based cancer registry data. Methods: An observational study was conducted of patients with stage 4 colon cancer identified from the National Cancer Data Base (2003-2005). Patients who underwent metastectomy were excluded. Patient, treatment, and hospital data were anal

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