Article
Acoustics
Zhongbo Sun, Jiajia Jiang, Yao Li, Chunyue Li, Zhuochen Li, Xiao Fu, Fajie Duan
Summary: An automated piecewise synthesis method is proposed in this study to automatically imitate various simple and complex cetacean tonal sounds with high similarity.
JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA
(2022)
Article
Optics
Jianwen Meng, Wenyi Ren, Ruoning Yu, Xu Ma, Gonzalo R. Arce, Dan Wu, Rui Zhang, Yingge Xie
Summary: Polarization image fusion is crucial in polarization imaging applications. Most existing algorithms focus on fusing intensity and degree of linear polarization, but overlook the information encoded in the angle of linear polarization. This study proposes a learning-based model to fuse polarization images and demonstrates its effectiveness through experiments.
OPTICS AND LASER TECHNOLOGY
(2024)
Article
Construction & Building Technology
Hafiz Suliman Munawar, Riya Aggarwal, Zakria Qadir, Sara Imran Khan, Abbas Z. Kouzani, M. A. Parvez Mahmud
Summary: Detecting buildings from high-resolution satellite imagery is crucial for various applications, but the diverse characteristics of buildings and their unplanned appearance in images present challenges for identification.
Article
Construction & Building Technology
Dimitrios Loverdos, Vasilis Sarhosis, Efstathios Adamopoulos, Anastasios Drougkas
Summary: The accuracy in transferring the real structure geometry to the numerical model is vital when modeling the mechanical behavior of existing masonry structures. Advances in photogrammetry and image processing have enabled the rapid and remote digital recording of objects and features. A proposed framework based on image processing automatically extracts geometrical features from masonry structures for advanced numerical modeling.
AUTOMATION IN CONSTRUCTION
(2021)
Article
Psychology, Experimental
Matthew D. Setzler, Robert L. Goldstone
Summary: Humans have a remarkable capacity for coordination, especially in interacting and acting jointly in groups. Collective music improvisation serves as a fascinating model domain for studying basic joint action mechanisms.
Article
Optics
Meiyun Chen, Zhiyong Zhang, Heng Wu, Shengli Xie, Han Wang
Summary: In this paper, we propose a method for center extraction of multi-spot images, which has been validated to be effective and feasible for high-precision positioning and sub-image segmentation in microlens array imaging system through numerical and actual experiments.
OPTICS AND LASERS IN ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Xiaofei Bian, Haiwei Pan, Kejia Zhang, Peng Liu, Chunling Chen
Summary: This paper proposes a method for the classification of malignant melanoma dermoscopy images based on multi-modal medical features, which can reduce the classification error caused by the complexity and subjectivity of visual interpretation and assist dermatologists in analyzing the skin lesion area.
IET IMAGE PROCESSING
(2023)
Article
Computer Science, Artificial Intelligence
Qili Chen, Ancai Zhang, Guangyuan Pan
Summary: This paper proposes a maximal-entropy-attention-based convolutional neural network (MEA-CNN) framework that utilizes a maximum entropy algorithm for image feature pre-extraction and an attention mechanism to enhance key areas of an image. Experimental results show that the proposed framework achieves high testing accuracy in tasks such as traffic sign recognition and road surface condition monitoring, and the extracted features are more easily interpretable.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Li-Na Jia, Ming-Yong Pang
Summary: The detection of edges in images is an important issue in image processing. This paper proposes a novel grey model based on a fractional-order discrete operator for detecting image edges. The model preprocesses the image, calculates the prediction, subtracts the preprocessed image from the predicted image, eliminates noise points, and finally extracts the image edges using discrete wavelet transform. The experimental results show that the proposed model accurately locates the image edges and has better anti-noise performance compared to traditional edge detection operators.
Article
Multidisciplinary Sciences
Tarek Helmy, Fahim Djatmiko
Summary: This paper presents an automatic framework for semantic annotation of images, utilizing convolutional neural networks to extract image features and recurrent neural networks to process surrounding text and generate annotation sentences. Experimental results show promising performance and comparability to recent image annotation systems.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2023)
Review
Chemistry, Multidisciplinary
Norberto E. Naal-Ruiz, Erick A. Gonzalez-Rodriguez, Gustavo Navas-Reascos, Rebeca Romo-De Leon, Alejandro Solorio, Luz M. Alonso-Valerdi, David I. Ibarra-Zarate
Summary: Mouth sounds have various applications in clinical diagnosis and emotional recognition. This review discusses different methods to apply, extract, analyze, and classify the acoustic features of mouth sounds. The most commonly analyzed features are in the time domain, such as zero-crossing rate, power/energy-based, and amplitude-based features, as well as tonal-based, spectral-based, and cepstral features in the frequency domain. Statistical tests like t-tests, variations of analysis of variance, and Pearson's correlation tests are used for feature evaluation, while machine learning methods like support vector machine and gaussian mixture models are used for pattern recognition. The main applications of mouth sound research are physical and mental condition monitoring, with other applications like communication also mentioned. Finally, the limitations of the studies are discussed, emphasizing the need for standard procedures for mouth sound acquisition and analysis.
APPLIED SCIENCES-BASEL
(2023)
Article
Optics
Qiang Wang, Liying Tan, Jing Ma
Summary: Positioning errors caused by wavefront distortion due to thermal deformation of optical systems are addressed in this study. A restoration algorithm is proposed to correct the beacon centroid for reducing pointing error in optical communication systems. The feasibility of the approach is verified through theoretical analysis and experimental verification, including in-orbit experiments, showing potential for designing inter-satellite laser communication systems.
OPTICS COMMUNICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Wei He, Quanming Yao, Chao Li, Naoto Yokoya, Qibin Zhao, Hongyan Zhang, Liangpei Zhang
Summary: In this paper, a unified paradigm combining spatial and spectral properties is proposed for hyperspectral image restoration. It achieves performance superiority through non-local spatial denoising and low-rank orthogonal basis exploration, while maintaining a low computational complexity.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2022)
Article
Chemistry, Multidisciplinary
Hyeongmo Gu, Seungyeon Choo
Summary: The construction industry has seen great progress in recent decades due to the use of computer programs, but labor productivity remains low compared to the manufacturing sector. To improve the efficiency of knowledge-based tasks, this study proposes a method to construct efficient facade datasets by collecting road-view images and automatically labeling them using deep learning. The study confirms that computers can extract significant facade information from images and verifies the characteristics of the building construction image datasets. By extracting facade design information from facades worldwide, this study suggests the possibility of securing both quantitative and qualitative facade design knowledge. The automation in the database construction process has shortened the overall time required.
APPLIED SCIENCES-BASEL
(2022)
Article
Mathematics
Zhaoxi Ma, Qin Zhao, Yiyun Zhu, Tianyou Cang, Xinhong Hei
Summary: This research introduces an intelligent method for extracting steel bar processing information using digital image processing technology and mathematical characteristics. The proposed method improves the intelligence of steel reinforcement engineering and provides a theoretical basis for the informationization of steel bar processing.
Article
Biology
Arik Kershenbaum, Todd M. Freeberg, David E. Gammon
JOURNAL OF THEORETICAL BIOLOGY
(2015)
Article
Ecology
Arik Kershenbaum, Ellen C. Garland
METHODS IN ECOLOGY AND EVOLUTION
(2015)
Article
Psychology, Biological
Arik Kershenbaum, Holly Root-Gutteridge, Bilal Habib, Janice Koler-Matznick, Brian Mitchell, Vicente Palacios, Sara Waller
BEHAVIOURAL PROCESSES
(2016)
Article
Multidisciplinary Sciences
Vlad Demartsev, Amiyaal Ilany, Arik Kershenbaum, Yair Geva, Ori Margalit, Inbar Schnitzer, Adi Barocas, Einat Bar-Ziv, Lee Koren, Eli Geffen
SCIENTIFIC REPORTS
(2017)
Editorial Material
Zoology
Arik Kershenbaum, Daniel T. Blumstein
Article
Zoology
Jessica L. Owens, Mariana Olsen, Amy Fontaine, Christopher Kloth, Arik Kershenbaum, Sara Waller
Article
Zoology
Arik Kershenbaum
BIOACOUSTICS-THE INTERNATIONAL JOURNAL OF ANIMAL SOUND AND ITS RECORDING
(2014)
Review
Biology
Arik Kershenbaum, Daniel T. Blumstein, Marie A. Roch, Caglar Akcay, Gregory Backus, Mark A. Bee, Kirsten Bohn, Yan Cao, Gerald Carter, Cristiane Caesar, Michael Coen, Stacy L. DeRuiter, Laurance Doyle, Shimon Edelman, Ramon Ferrer-i-Cancho, Todd M. Freeberg, Ellen C. Garland, Morgan Gustison, Heidi E. Harley, Chloe Huetz, Melissa Hughes, Julia Hyland Bruno, Amiyaal Ilany, Dezhe Z. Jin, Michael Johnson, Chenghui Ju, Jeremy Karnowski, Bernard Lohr, Marta B. Manser, Brenda McCowan, Eduardo Mercado, Peter M. Narins, Alex Piel, Megan Rice, Roberta Salmi, Kazutoshi Sasahara, Laela Sayigh, Yu Shiu, Charles Taylor, Edgar E. Vallejo, Sara Waller, Veronica Zamora-Gutierrez
BIOLOGICAL REVIEWS
(2016)
Article
Ecology
Arik Kershenbaum, Lior Blank, Iftach Sinai, Juha Merila, Leon Blaustein, Alan R. Templeton
Article
Biology
Arik Kershenbaum, Ann E. Bowles, Todd M. Freeberg, Dezhe Z. Jin, Adriano R. Lameira, Kirsten Bohn
PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
(2014)
Article
Behavioral Sciences
Vlad Demartsev, Arik Kershenbaum, Amiyaal Ilany, Adi Barocas, Yishai Weissman, Lee Koren, Eli Geffen
Article
Ecology
Arik Kershenbaum, Vlad Demartsev, David E. Gammon, Eli Geffen, Morgan L. Gustison, Amiyaal Ilany, Adriano R. Lameira
Summary: Information complexity in animals is an indicator of advanced communication and intricate socio-ecology. Estimating Zipf's law coefficient using entropy approach is more accurate than the traditional method, providing a robust way to investigate the evolution of communication systems in animals.
METHODS IN ECOLOGY AND EVOLUTION
(2021)
Article
Ecology
Elisabeth Bru, Bethany R. Smith, Hannah Butkiewicz, Amy C. Fontaine, Angela Dassow, Jessica L. Owens, Holly Root-Gutteridge, Loretta Schindler, Arik Kershenbaum
Summary: This study demonstrates the use of acoustic localization and high-resolution land cover classification to study the ecology of vocalizing animals in the wild. The results show differences in vocal behavior between coyotes and wolves, with coyotes vocalizing closer to human features and wolves vocalizing further away. This method can be used for monitoring vocally active animals at larger scales.
Article
Ecology
Bethany R. Smith, Holly Root-Gutteridge, Hannah Butkiewicz, Angela Dassow, Amy C. Fontaine, Andrew Markham, Jessica Owens, Loretta Schindler, Matthew Wijers, Arik Kershenbaum
Summary: This study compared the efficacy of low-cost and high-end acoustic recorders in detecting and localizing wildlife and domestic animals vocalizations. Results showed that while the sensitivity of low-cost recorders was lower, their ability to localize vocalizations when detected was comparable to high-end recorders in terms of precision and maximum detection ranges.
Article
Zoology
Arik Kershenbaum, Eloise C. Deaux, Bilal Habib, Brian Mitchell, Vicente Palacios, Holly Root-Gutteridge, Sara Waller
BIOACOUSTICS-THE INTERNATIONAL JOURNAL OF ANIMAL SOUND AND ITS RECORDING
(2018)