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Journal articles on the topic 'Ambiguity detection'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Schmitz, Sylvain. "An experimental ambiguity detection tool." Science of Computer Programming 75, no. 1-2 (2010): 71–84. http://dx.doi.org/10.1016/j.scico.2009.07.002.

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Schmitz, Sylvain. "An Experimental Ambiguity Detection Tool." Electronic Notes in Theoretical Computer Science 203, no. 2 (2008): 69–84. http://dx.doi.org/10.1016/j.entcs.2008.03.045.

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3

KAMOWSKI-SHAKIBAI, MARGARET T., and HELEN SMITH CAIRNS. "Kindergarten children can be taught to detect lexical ambiguities." Journal of Child Language 43, no. 2 (2015): 442–56. http://dx.doi.org/10.1017/s030500091500015x.

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ABSTRACTThis study investigates the development of metalinguistic skills, particularly ambiguity detection, and whether training accelerates this development for prereaders in kindergarten (5;5–6;6). It is the first to compare homophone detection with lexically ambiguous sentence detection in which the same homophones appear. The experimental group received ambiguity detection training; the control group received vocabulary training. Results showed that there is a spontaneous development of homophone detection abilities at the end of kindergarten, and training may accelerate this trajectory. T

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Liu, Jiangyi, Fengmin Zhu, and Fei He. "Automated Ambiguity Detection in Layout-Sensitive Grammars." Proceedings of the ACM on Programming Languages 7, OOPSLA2 (2023): 1150–75. http://dx.doi.org/10.1145/3622838.

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Layout-sensitive grammars have been adopted in many modern programming languages. In a serious language design phase, the specified syntax—typically a grammar—must be unambiguous. Although checking ambiguity is undecidable for context-free grammars and (trivially also) layout-sensitive grammars, ambiguity detection , on the other hand, is possible and can benefit language designers from exposing potential design flaws . In this paper, we tackle the ambiguity detection problem in layout-sensitive grammars. Inspired by a previous work on checking the bounded ambiguity of context-free grammars vi

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Liu, Yang, Alan Medlar, and Dorota Głowacka. "Lexical ambiguity detection in professional discourse." Information Processing & Management 59, no. 5 (2022): 103000. http://dx.doi.org/10.1016/j.ipm.2022.103000.

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Meyer, Marie-Christine, and Uli Sauerland. "A pragmatic constraint on ambiguity detection." Natural Language & Linguistic Theory 27, no. 1 (2008): 139–50. http://dx.doi.org/10.1007/s11049-008-9060-2.

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Hayman Oo, Khin, Azlin Nordin, Amelia Ritahani Ismail, and Suriani Sulaiman. "An Analysis of Ambiguity Detection Techniques for Software Requirements Specification (SRS)." International Journal of Engineering & Technology 7, no. 2.29 (2018): 501. http://dx.doi.org/10.14419/ijet.v7i2.29.13808.

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Ambiguity is the major problem in Software Requirements Specification (SRS) documents because most of the SRS documents are written in natural language and natural language is generally ambiguous. There are various types of techniques that have been used to detect ambiguity in SRS documents. Based on an analysis of the existing work, the ambiguity detection techniques can be categorized into three approaches: (1) manual approach, (2) semi-automatic approach using natural language processing, (3) semi-automatic approach using machine learning. Among them, one of the semi-automatic approaches th

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Sun, Xiping, Xipeng Wu, Qinquan Zhou, Lei Zhang, and Jianxin Wu. "Airborne Radar Staggered PRF Coherent Processing Method for Down-Looking Target Detection." Remote Sensing 15, no. 13 (2023): 3271. http://dx.doi.org/10.3390/rs15133271.

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Airborne radar plays a crucial role in detecting aerial targets, but its detection capability can be significantly affected by strong ground clutter when operating in down-looking mode. The range-Doppler (RD) results of ground clutter in airborne radar may overlap the range-Doppler results of the targets, causing target occlusion and rendering them undetectable. In addition to target detection, accurate extraction of target parameters is also of great importance. Due to the high-speed movement of the airborne platform, targets may exhibit range-Doppler ambiguity, necessitating the use of appro

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Shaukat, Sundus, Kashif Ayyub, Wasif Nisar, Mudassar Raza, and Tariq Umer. "Ambiguity Detection Methods in Context Free Grammar." Research Journal of Applied Sciences, Engineering and Technology 7, no. 22 (2014): 4652–55. http://dx.doi.org/10.19026/rjaset.7.847.

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Tesar, Bruce. "Using Inconsistency Detection to Overcome Structural Ambiguity." Linguistic Inquiry 35, no. 2 (2004): 219–53. http://dx.doi.org/10.1162/002438904323019057.

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The Inconsistency Detection Learner (IDL) is an algorithm for language learning that addresses the problem of structural ambiguity.If an overt form is structurally ambiguous, the learner must be capable of inferring which interpretation of the overt form is correct by reference to other overt data of the language.The IDL does this by attempting to construct grammars for combinations of interpretations of the overt forms, and discarding those combinations that are inconsistent. The potential of this algorithm for overcoming the combinatorial growth in combinations of interpretations is supporte

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Dar, Hafsa, Romana Aziz, Javed Ali Khan, Muhammad IkramUllah Lali, and Nouf Abdullah Almujally. "Gamify4LexAmb: a gamification-based approach to address lexical ambiguity in natural language requirements." PeerJ Computer Science 10 (September 19, 2024): e2229. http://dx.doi.org/10.7717/peerj-cs.2229.

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Ambiguity is a common challenge in specifying natural language (NL) requirements. One of the reasons for the occurrence of ambiguity in software requirements is the lack of user involvement in requirements elicitation and inspection phases. Even if they get involved, it is hard for them to understand the context of the system, and ultimately unable to provide requirements correctly due to a lack of interest. Previously, the researchers have worked on ambiguity avoidance, detection, and removal techniques in requirements. Still, less work is reported in the literature to actively engage users i

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Mao, Yitong, Chong Song, and Bingnan Wang. "Algorithm for the Weak Target Joint Detection and Ambiguity Resolution Based on Ambiguity Matrix." Remote Sensing 16, no. 9 (2024): 1597. http://dx.doi.org/10.3390/rs16091597.

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The looking-down mode of space airship bistatic radars faces complex sea–land clutter, and the mode of wide-range surveillance and the over-sight detection of the satellite platform generates a low SNR and range–Doppler ambiguity. The method traditionally used involves the transmission of multiple Pulse Repetition Frequencies (PRFs) and correlating them to solve the ambiguity. However, with a low SNR, the traditional disambiguation fails due to the large number of false alarms and target omissions. In order to solve this problem, a new algorithm for multi-target joint detection and range–Doppl

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Tao Li, Tao Li, Yu Wang Tao Li, Zheng Zhang Yu Wang, Xuezhuan Zhao Zheng Zhang, and Lishen Pei Xuezhuan Zhao. "Visual Object Detection with Score Refinement." 網際網路技術學刊 23, no. 5 (2022): 1163–72. http://dx.doi.org/10.53106/160792642022092305025.

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<p>Robustness of object detection against hard samples, especially small objects, has long been a critical and difficult problem that hinders development of convolutional object detectors. To address this issue, we propose Progressive Refinement Network to reduce classification ambiguity for scale robust object detection. In PRN, several orders of residuals for the class prediction are regressed from upper level contexts and the residuals are progressively added to the basic prediction stage by stage, yielding multiple refinements. Supervision signal is imposed at each stage and an integ

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Zhou, Gangbing, Ze Yu, Xianxun Yao, and Jindong Yu. "An Azimuth Ambiguity Suppression Method for SAR Based on Time-Frequency Joint Analysis." Remote Sensing 17, no. 13 (2025): 2327. https://doi.org/10.3390/rs17132327.

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Azimuth ambiguity caused by spectral aliasing severely degrades the quality of Synthetic Aperture Radar (SAR) images. To suppress azimuth ambiguity while preserving image details as much as possible, this paper proposes an azimuth ambiguity suppression method for SAR based on time-frequency joint analysis. By exploiting the distribution differences of ambiguous signals across different sub-spectra, the method locates azimuth ambiguity in the time domain through multi-sub-spectrum change detection and fusion, followed by ambiguity suppression in the azimuth time-frequency domain. Experimental r

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Muhamad, Fatin Nur Jannah, Siti Hafizah Ab Hamid, Hema Subramaniam, Razailin Abdul Rashid, and Faisal Fahmi. "Fault-Prone Software Requirements Specification Detection Using Ensemble Learning for Edge/Cloud Applications." Applied Sciences 13, no. 14 (2023): 8368. http://dx.doi.org/10.3390/app13148368.

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Ambiguous software requirements are a significant contributor to software project failure. Ambiguity in software requirements is characterized by the presence of multiple possible interpretations. As requirements documents often rely on natural language, ambiguity is a frequent challenge in industrial software construction, with the potential to result in software that fails to meet customer needs and generates issues for developers. Ambiguities arise from grammatical errors, inappropriate language use, multiple meanings, or a lack of detail. Previous studies have suggested the use of supervis

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Dwivedi, Sanjay K. "A Highest Sense Count Based Method for Disambiguation of Web Queries for Hindi Language Web Information Retrieval." International Journal of Information Retrieval Research 2, no. 4 (2012): 1–11. http://dx.doi.org/10.4018/ijirr.2012100101.

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The ambiguity in word senses has been recognized as a major challenge for the information retrieval systems. Hindi language web information retrieval, like other languages, faces the problem of sense ambiguity. The sense ambiguity problem deteriorates the performance of every natural language processing (NLP) application. The performance of Hindi language web information retrieval is also affected by it. In this paper, the author formalized an approach for the disambiguation of the senses to improve the performance of Hindi web information retrieval. Our system works in such a way that ambigui

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Pandey, Hari Mohan. "Advances in Ambiguity Detection Methods for Formal Grammars." Procedia Engineering 24 (2011): 700–707. http://dx.doi.org/10.1016/j.proeng.2011.11.2722.

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Gillis, Randall, and Elizabeth S. Nilsen. "Cognitive flexibility supports preschoolers’ detection of communicative ambiguity." First Language 34, no. 1 (2014): 58–71. http://dx.doi.org/10.1177/0142723714521839.

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Liang, Junxiong, Pei An, and Jie Ma. "Distribution Aware VoteNet for 3D Object Detection." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 2 (2022): 1583–91. http://dx.doi.org/10.1609/aaai.v36i2.20049.

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Occlusion is common in the actual 3D scenes, causing the boundary ambiguity of the targeted object. This uncertainty brings difficulty for labeling and learning. Current 3D detectors predict the bounding box directly, regarding it as Dirac delta distribution. However, it does not fully consider such ambiguity. To deal with it, distribution learning is used to efficiently represent the boundary ambiguity. In this paper, we revise the common regression method by predicting the distribution of the 3D box and then present a distribution-aware regression (DAR) module for box refinement and localiza

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Böning, Vincent G. A. "Ambiguity of the Solar Meridional Flow." Proceedings of the International Astronomical Union 13, S340 (2018): 13–14. http://dx.doi.org/10.1017/s1743921318001837.

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AbstractRecent helioseismic estimates of the deep solar meridional flow have been contradictory. Using two years worth of GONG data, I show here that the detection of the meridional flow is ambiguous below about 0.85 solar radii.

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Chen, Qusen, Hua Chen, Weiping Jiang, Xiaohui Zhou, and Peng Yuan. "A New Cycle Slip Detection and Repair Method for Single-Frequency GNSS Data." Journal of Navigation 71, no. 6 (2018): 1492–510. http://dx.doi.org/10.1017/s0373463318000243.

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Cycle slip detection for single frequency Global Navigation Satellite System (GNSS) data is currently mainly based on measurement modelling or prediction, which cannot be effectively performed for kinematic applications and it is difficult to detect or repair small cycle slips such as half-cycle slips. In this paper, a new method that is based on the total differential of ambiguity and Least-Squares Adjustment (LSA) for cycle slip detection and repair is introduced and validated. This method utilises only carrier-phase observations to build an ambiguity function. LSA is then conducted for dete

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22

Reinecke, David, and Jordan Bimm. "The maintenance of ambiguity in Martian exobiology." Social Studies of Science 52, no. 2 (2022): 199–226. http://dx.doi.org/10.1177/03063127221077207.

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How do scientists maintain their research programs in the face of not finding anything? Continual failure to produce results can result in declining support, scientific controversy and credibility challenges. We elaborate on a crucial mechanism for sustaining the credibility of research programs through periods of non-detection: the maintenance of ambiguity. By this, we refer to scientific strategies that resist closure or an experiment’s premature end by creating doubt in negative findings and fostering hope for future positive results. To illustrate this concept, we draw upon the recent hist

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JOZWIK, SARA L., and KAREN H. DOUGLAS. "Effects of Semantic Ambiguity Detection Training on Reading Comprehension Achievement of English Learners With Learning Difficulties." Multiple Voices for Ethnically Diverse Exceptional Learners 16, no. 2 (2016): 37–57. http://dx.doi.org/10.56829/1547-1888.16.2.37.

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This study examined how explicit instruction in semantic ambiguity detection affected the reading comprehension and metalinguistic awareness of five English learners (ELs) with learning difficulties (e.g., attention deficit/hyperactivity disorder, specific learning disability). A multiple probe across participants design (Gast & Ledford, 2010) evaluated instructional effects on (a) number of correct replacements (CR) on maze tasks and (b) percentage accuracy with applying targeted metalinguistic awareness skills on researcher-developed semantic ambiguity detection probes. During the baseli

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Zuo, Luo, Nan Li, Jie Tan, et al. "A Coherent Integration Method for Moving Target Detection in Frequency Agile Signal-Based Passive Bistatic Radar." Remote Sensing 16, no. 7 (2024): 1148. http://dx.doi.org/10.3390/rs16071148.

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In this paper, the possibility of improving target detection performance in passive bistatic radar by exploiting a frequency agile (FA) signal is investigated, namely frequency agile signal-based passive bistatic radar (FAPBR) coherent integration. Since the carrier frequency of each pulse signal is agile, FAPBR coherent integration suffers from the problems of random range and Doppler phase fluctuations. To tackle these challenges, a novel FA signal coherent integration target detection scheme for PBR is proposed. In particular, the phase quadratic difference principle is presented for elimin

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Minsheng Wang, A. K. Chan, and C. K. Chui. "Linear frequency-modulated signal detection using Radon-ambiguity transform." IEEE Transactions on Signal Processing 46, no. 3 (1998): 571–86. http://dx.doi.org/10.1109/78.661326.

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Sencar, Husrev Taha, and Nasir Memon. "Combatting Ambiguity Attacks via Selective Detection of Embedded Watermarks." IEEE Transactions on Information Forensics and Security 2, no. 4 (2007): 664–82. http://dx.doi.org/10.1109/tifs.2007.908211.

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Robbins, Joanne K., T. V. Joe Layng, and Hilary Jo Karp. "Ambiguity and the abstract tact: A signal detection analysis." Analysis of Verbal Behavior 12, no. 1 (1995): 1–11. http://dx.doi.org/10.1007/bf03392893.

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Pelikan, Martin, Hana Stikova, and Ivan Vrana. "Detection of Resource Overload in Conditions of Project Ambiguity." IEEE Transactions on Fuzzy Systems 25, no. 4 (2017): 868–77. http://dx.doi.org/10.1109/tfuzz.2016.2584645.

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Nepeivoda, Antonina Nikolaevna, Yulia Andreevna Belikova, Kirill Konstantinovich Shevchenko, et al. "REDoS Detection in “Domino” Regular Expressions by Ambiguity Analysis." Proceedings of the Institute for System Programming of the RAS 35, no. 3 (2023): 109–24. http://dx.doi.org/10.15514/ispras-2023-35(3)-8.

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The Regular Expression Denial of Service (REDoS) problem refers to a time explosion caused by the high computational complexity of matching a string against a regex pattern. This issue is prevalent in popular regex engines, such as PYTHON, JAVASCRIPT, and C++. In this paper, we examine several existing open-source tools for detecting REDoS and identify a class of regexes that can create REDoS situations in popular regex engines but are not detected by these tools. To address this gap, we propose a new approach based on ambiguity analysis, which combines a strong star-normal form test with an a

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Zahrin, Mohd Firdaus, Mohd Hafeez Osman, Sa'adah Hassan, Azlena Haron, and Alfian Abdul Halin. "Ambiguity Detection and Improvement for Malay Requirements Specification: A Systematic Review." International Journal on Advanced Science, Engineering and Information Technology 13, no. 6 (2023): 2294–301. http://dx.doi.org/10.18517/ijaseit.13.6.18535.

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Malaysian public sectors have invested billions in digitizing systems. Electronic government efforts created much software. Our informal interview taught us that many software projects encountered delays, and several failed. One of the main contributions of software failure is ambiguity in requirements specification (RS). Ambiguity is a familiar requirement smell that causes misinterpretation. Thus, we seek to devise a technique for detecting and improving ambiguous RS in the Malaysian public sector. One of our challenges is that the Malaysian public sector RS is developed in Malay, and most a

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McMahon, Sean, and Julie Cosmidis. "False biosignatures on Mars: anticipating ambiguity." Journal of the Geological Society 179, no. 2 (2021): jgs2021–050. http://dx.doi.org/10.1144/jgs2021-050.

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It is often acknowledged that the search for life on Mars might produce false positive results, particularly via the detection of objects, patterns or substances that resemble the products of life in some way but are not biogenic. The success of major current and forthcoming rover missions now calls for significant efforts to mitigate this risk. Here, we review known processes that could have generated false biosignatures on early Mars. These examples are known largely from serendipitous discoveries rather than systematic research and remain poorly understood; they probably represent only a sm

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Zhao, Wei, and Bao An Hao. "Blind Detection with Deterministic Arrange and Scale to Underwater Acoustic Source." Applied Mechanics and Materials 380-384 (August 2013): 854–59. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.854.

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t is a valid anti-interference method that blindly separates the contaminated radiant acoustic source object from interferences, but the separated radiant acoustic source object with arrange and scale ambiguity makes the likelihood ratio detection impossible. This paper solves the ambiguity problems by utilizing the correlation and energy consistency of the same source in the same overlapped frame data; Known delay distance, data sum length and signal to noise ratio (SNR), the paper analyzes algorithms performance and draws the receiver operating characteristic (ROC) curve in different distanc

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Zhang, Peixin, Jianxin Wang, Peng Ren, Shushu Yang, and Haiwei Song. "Improved ASM-TER Training Sequence Detection and Fine Doppler Frequency Estimation Methods from a Satellite." Journal of Sensors 2020 (June 8, 2020): 1–11. http://dx.doi.org/10.1155/2020/3625184.

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To detect terrestrial application-specific messages (ASM-TER) signals from a satellite, a novel detection method based on the fast computation of the cross ambiguity function is proposed in this paper. The classic cross ambiguity function’s computational burden is heavy, and we transform the classic cross ambiguity function to a frequency domain version to reduce the computational complexity according to Parseval’s theorem. The computationally efficient sliding discrete Fourier transform (SDFT) is utilized to calculate the frequency spectrum of the windowed received signal, from which the Dopp

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Deng, Jian, Aiguo Zhang, Nenghui Zhu, and Fuyang Ke. "Extra-Wide Lane Ambiguity Resolution and Validation for a Single Epoch Based on the Triple-Frequency BeiDou Navigation Satellite System." Sensors 20, no. 5 (2020): 1534. http://dx.doi.org/10.3390/s20051534.

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The ambiguity resolution (AR) and validation of the global navigation satellite system (GNSS) have been challenging tasks for some decades. Considering the reliability problem of extra-wide-lane (EWL) ambiguity in the triple-carrier ambiguity resolution (TCAR), a method for validating the reliability of the EWL ambiguity using a single epoch was proposed for the BeiDou Navigation Satellite System (BDS). For the initial EWL ambiguity, obtained using a rounding estimator with a geometry-free (GF) model, the double-difference ionospheric delay was first estimated to construct a relative positioni

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Shiihara, Hideki, Shozo Sonoda, Hiroto Terasaki, et al. "Wayfinding artificial intelligence to detect clinically meaningful spots of retinal diseases: Artificial intelligence to help retina specialists in real world practice." PLOS ONE 18, no. 3 (2023): e0283214. http://dx.doi.org/10.1371/journal.pone.0283214.

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Aim/background To aim of this study is to develop an artificial intelligence (AI) that aids in the thought process by providing retinal clinicians with clinically meaningful or abnormal findings rather than just a final diagnosis, i.e., a “wayfinding AI.” Methods Spectral domain optical coherence tomography B-scan images were classified into 189 normal and 111 diseased eyes. These were automatically segmented using a deep-learning based boundary-layer detection model. During segmentation, the AI model calculates the probability of the boundary surface of the layer for each A-scan. If this prob

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Ma, Yanting, Joshua Rapp, Petros Boufounos, and Hassan Mansour. "A model of spatial resolution uncertainty for Compton camera imaging." EPJ Web of Conferences 288 (2023): 10002. http://dx.doi.org/10.1051/epjconf/202328810002.

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Compton cameras use a pair of detectors to record the energy deposited during Compton scattering and photoabsorption of gamma ray photons. By inverting the forward model for these detection events, the 3D radioactive source distribution can be recovered computationally. However, existing methods of describing the forward model ignore the ambiguity in the Compton cone axis introduced by the detector pixel size. In this paper, we introduce approximations to the axis ambiguity that make the description of the source ambiguity computationally tractable and improve the accuracy of the detection for

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Pittke, Fabian, Henrik Leopold, and Jan Mendling. "Automatic Detection and Resolution of Lexical Ambiguity in Process Models." IEEE Transactions on Software Engineering 41, no. 6 (2015): 526–44. http://dx.doi.org/10.1109/tse.2015.2396895.

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Zuo, Lei, Ming Li, Zheng Liu, and Runqing Cao. "Range‐spread target detection based on the matched ambiguity function." IET Radar, Sonar & Navigation 10, no. 7 (2016): 1213–19. http://dx.doi.org/10.1049/iet-rsn.2015.0475.

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Szabo Wankoff, Lorain, and Helen Smith Cairns. "Why Ambiguity Detection Is a Predictor of Early Reading Skill." Communication Disorders Quarterly 30, no. 3 (2008): 183–92. http://dx.doi.org/10.1177/1525740108324096.

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Zhang, Qilei, Zhen Dong, and Dexin Li. "Optimal Detection and Ambiguity Function of Hybrid Distributed MIMO Radar." IEEE Access 7 (2019): 160786–99. http://dx.doi.org/10.1109/access.2019.2951724.

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Basten, H. J. S. "The Usability of Ambiguity Detection Methods for Context-Free Grammars." Electronic Notes in Theoretical Computer Science 238, no. 5 (2009): 35–46. http://dx.doi.org/10.1016/j.entcs.2009.09.039.

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Wang, Yue, Yan Piao, Haowen Wang, Hao Zhang, and Bing Li. "An Improved Forest Smoke Detection Model Based on YOLOv8." Forests 15, no. 3 (2024): 409. http://dx.doi.org/10.3390/f15030409.

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This study centers on leveraging smoke detection for preemptive forest smoke detection. Owing to the inherent ambiguity and uncertainty in smoke characteristics, existing smoke detection algorithms suffer from reduced detection accuracy, elevated false alarm rates, and occurrences of omissions. To resolve these issues, this paper employs an efficient YOLOv8 network and integrates three novel detection modules for enhancement. These modules comprise the edge feature enhancement module, designed to identify smoke ambiguity features, alongside the multi-feature extraction module and the global fe

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Zz, Mi, C. Cong, Y. Cheng, and Zhang Hm. "Study on defects detection technique of precise optical element." E3S Web of Conferences 53 (2018): 01037. http://dx.doi.org/10.1051/e3sconf/20185301037.

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Aiming at the problems of low efficiency of traditional detection methods for surface defects of precision optical element and inconvenient detection for optical elements of different calibers, a adjustable optical element defects detecting device for large laser devices is designed. The key technical points of system composition, detection environment, illumination design and image stitching are expounded. According to the characteristics of surface defects of optical element, such as the difference of contour, gray scale, contrast and ambiguity, a classification method based on FCM is propos

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Zhuang, Z., and P. M. Frank. "Qualitative observer and its application to fault detection and isolation systems." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 211, no. 4 (1997): 253–62. http://dx.doi.org/10.1243/0959651971539786.

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Qualitative simulation is one of the main techniques in qualitative reasoning. It has the great potential to solve engineering problems, if only the difficulty of ambiguity can be overcome. On the other hand, in many applications measurements are often available. In this paper a qualitative observer is proposed, which is based on qualitative simulation and applied using a novel technique: observation filtering. This provides a framework in which the measured information can be utilized to reduce accumulated ambiguity and to avoid spurious solutions. Simulated results of qualitative simulation

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Jia, Wei, Yuan Feng, Xingshuai Qiao, Tianrun Wang, and Tao Shan. "Variable Doppler Starting Point Keystone Transform for Radar Maneuvering Target Detection." Remote Sensing 16, no. 12 (2024): 2129. http://dx.doi.org/10.3390/rs16122129.

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The Doppler band compensated by the keystone transform (KT) is limited. Therefore, it needs to be used in conjunction with the Doppler ambiguity compensation function to correct the range migration (RM) caused by maneuvering targets with Doppler ambiguity. However, the KT implemented by sinc interpolation suffers from significant performance loss at boundaries of compensation Doppler bands. Additionally, in a multi-target scenario, KT implementation methods occupy high complexity when the Doppler range of targets spans over two compensation Doppler bands. To address the aforementioned issues,

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Wu, Shujie, Wei Wang, Jie Deng, et al. "Nearshore Ship Detection in PolSAR Images by Integrating Superpixel-Level GP-PNF and Refined Polarimetric Decomposition." Remote Sensing 16, no. 6 (2024): 1095. http://dx.doi.org/10.3390/rs16061095.

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Nearshore ship detection has significant applications in both the military and civilian domains. Compared to synthetic aperture radar (SAR), polarimetric synthetic aperture radar (PolSAR) provides richer information for analyzing the scattering mechanisms of ships and enables better detection of ship targets. However, ships in nearshore areas tend to be highly concentrated, and ship detection is often affected by adjacent strong scattering, resulting in false alarms or missed detections. While the GP-PNF detector performs well in PolSAR ship detection, it cannot obtain satisfactory results in

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Brody, Justin. "Neurosymbolic Visual Reasoning for Ambiguity Resolution." Proceedings of the AAAI Symposium Series 5, no. 1 (2025): 308–16. https://doi.org/10.1609/aaaiss.v5i1.35606.

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While modern computer vision systems have notched tremendous successes there are still obstacles to deploying such systems in real-world scenarios. Two salient obstacles are the lack of flexibility that comes with systems trained on fixed categories of data and a lack of stability. Indeed, it is not uncommon when using a pre-trained classifier on a video stream to find it will correctly identify an object as a tree (for example) in one frame only to fail to identify the same object as a tree in the next. In this paper we propose a system that can ameliorate both of these issues by introducing

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Prasannakumar, Aswathy, and Deepak Mishra. "Deep Efficient Data Association for Multi-Object Tracking: Augmented with SSIM-Based Ambiguity Elimination." Journal of Imaging 10, no. 7 (2024): 171. http://dx.doi.org/10.3390/jimaging10070171.

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Recently, to address the multiple object tracking (MOT) problem, we harnessed the power of deep learning-based methods. The tracking-by-detection approach to multiple object tracking (MOT) involves two primary steps: object detection and data association. In the first step, objects of interest are detected in each frame of a video. The second step establishes the correspondence between these detected objects across different frames to track their trajectories. This paper proposes an efficient and unified data association method that utilizes a deep feature association network (deepFAN) to lear

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Xu, Yuezhu, He Wang, Yuan Bi, Guohao Nie, and Xingmei Wang. "MCDet: Target-Aware Fusion for RGB-T Fire Detection." Forests 16, no. 7 (2025): 1088. https://doi.org/10.3390/f16071088.

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Forest fire detection is vital for ecological conservation and disaster management. Existing visual detection methods exhibit instability in smoke-obscured or illumination-variable environments. Although multimodal fusion has demonstrated potential, effectively resolving inconsistencies in smoke features across diverse modalities remains a significant challenge. This issue stems from the inherent ambiguity between regions characterized by high temperatures in infrared imagery and those with elevated brightness levels in visible-light imaging systems. In this paper, we propose MCDet, an RGB-T f

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Botella, C., J. Ferré, and R. Boqué. "Outlier detection and ambiguity detection for microarray data in probabilistic discriminant partial least squares regression." Journal of Chemometrics 24, no. 7-8 (2010): 434–43. http://dx.doi.org/10.1002/cem.1304.

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