Article
Engineering, Electrical & Electronic
Shobhana Periyasamy, Aruna Prakasarao, M. Menaka, B. Venkatraman, M. Jayashree
Summary: Thermography is a non-invasive approach for breast cancer screening, aiming to detect the disease early through interpretation of thermal images. However, the lack of standardization in imaging protocols and interpretation systems worldwide has limited the progression of this technique.
IEEE SENSORS JOURNAL
(2021)
Article
Materials Science, Multidisciplinary
Y. Uchida, T. Kanade, D. Shiozawa, T. Sakagami
Summary: This study proposes a method for thermoelastic stress analysis that does not require a reference signal and frequency analysis, but still achieves comparable or higher accuracy in obtaining stress amplitude distribution compared to self-correlation lock-in thermography. The method involves generating an observation matrix from thermal fluctuations caused by stress and using singular value decomposition (SVD) to extract stress amplitude distribution and the original load signal. Experimental results show that the proposed method yields equivalent stress amplitude distribution to conventional lock-in thermography and successfully reconstructs the original load signal.
EXPERIMENTAL MECHANICS
(2023)
Article
Materials Science, Characterization & Testing
Amirreza Ardebili, Mohammad Hossein Alaei
Summary: This study investigates the functional role of step-heating thermography in the detection of delamination defects in multi-layer GFRP composite patches. The results show that all defects in both 4 and 8 layer laminates can be identified, with higher dimensional accuracy in 8 layer patches.
NDT & E INTERNATIONAL
(2022)
Review
Agriculture, Dairy & Animal Science
Daniel Mota-Rojas, Alfredo M. F. Pereira, Julio Martinez-Burnes, Adriana Dominguez-Oliva, Patricia Mora-Medina, Alejandro Casas-Alvarado, Jennifer Rios-Sandoval, Ana de Mira Geraldo, Dehua Wang
Summary: This article reviews the importance of infrared thermography in evaluating the thermal response and health status of wildlife species. Due to the different characteristics of wildlife species, thermal windows have not been established yet, so precise application is required for different animal species. The application of infrared thermography in zoos and conservation centers can help determine and monitor habitat designs to meet the specific needs of animals.
Article
Agriculture, Dairy & Animal Science
Alejandro Casas-Alvarado, Julio Martinez-Burnes, Patricia Mora-Medina, Ismael Hernandez-Avalos, Adriana Dominguez-Oliva, Karina Lezama-Garcia, Jocelyn Gomez-Prado, Daniel Mota-Rojas
Summary: Infrared thermography is a non-invasive diagnostic method that evaluates thermal and circulatory changes in companion animals. It can be used to diagnose inflammatory and neoplastic conditions early. However, there is disagreement about the effectiveness of the thermal windows used in dogs and cats.
Article
Engineering, Multidisciplinary
M. Mint Brahim, A. Godin, M. Azaiez, E. Palomo Del Barrio
Summary: A new method for estimating the thermal properties of composite materials is proposed, utilizing Karhunen-Loeve decomposition techniques combined with infrared thermography experiments. The introduction of two techniques based on test functions extends the method to cases where the morphology of the composite material is not straightforward, proving effectiveness and accuracy through numerical tests.
INVERSE PROBLEMS IN SCIENCE AND ENGINEERING
(2021)
Article
Agriculture, Dairy & Animal Science
Antonio Verduzco-Mendoza, Antonio Bueno-Nava, Dehua Wang, Julio Martinez-Burnes, Adriana Olmos-Hernandez, Alejandro Casas, Adriana Dominguez, Daniel Mota-Rojas
Summary: Infrared thermography is a useful tool for assessing the pathological or stressful states of laboratory animals, but the sensitivity and specificity of thermal windows are still controversial. Evaluating the health and thermal stability of laboratory animals is crucial for experimental designs.
Article
Biology
Mireia Munoz-Alcami, Jose Ignacio Priego-Quesada, Marc Gimeno Raga, Alvaro Duran Lozano, Marina Gil-Calvo
Summary: This study examines changes in anterior thigh skin temperature in response to a cold stress test after a strength exercise fatiguing protocol. The results indicate that fatigue from strength exercise results in lower skin temperature and faster thermal increase after a cold stress test.
JOURNAL OF THERMAL BIOLOGY
(2021)
Article
Chemistry, Multidisciplinary
Samuel Klein, Henrique Fernandes, Hans-Georg Herrmann
Summary: This study investigates the application of lock-in thermography for solar loading thermography, highlighting the suitability of calculations based on area sources for large-scale structures. It provides an overview of extended source approximation formulas for determining material properties and demonstrates the practical application in estimating thermal effusivity of a retaining wall structure subject to natural outside heating phenomena.
APPLIED SCIENCES-BASEL
(2021)
Article
Instruments & Instrumentation
Ahmed ElSheikh, Natali Barakat, Bassam A. Abu-Nabah, Mohammad O. Hamdan
Summary: This study proposes a simple one-dimensional thermography technique to estimate the thermal diffusivity of metallic alloys. A theoretical model is developed and validated to account for sample dimensions and material properties, and experimental validation is done on tempered aluminum alloy and annealed stainless steel alloy, showing an uncertainty lower than 2% in material thermal diffusivity estimation.
INFRARED PHYSICS & TECHNOLOGY
(2022)
Article
Environmental Sciences
Jing Fang, Taiyong Mao, Fuyu Bo, Bomeng Hao, Nan Zhang, Shaohai Hu, Wenfeng Lu, Xiaofeng Wang
Summary: This paper proposes a 3D SAR image despeckling method based on searching for similar patches and applying the high-order singular value decomposition (HOSVD) theory. The method extends 2D to 3D for SAR image despeckling using tensor patches, uses a new non-local similar patch-searching measure criterion to classify patches, and stacks similar patches into 3D tensors. Lastly, the iterative adaptive weighted tensor cyclic approximation is used for SAR image despeckling based on the HOSVD method. Experimental results demonstrate that the proposed method effectively reduces speckle noise and preserves fine details.
Article
Thermodynamics
Seon-In Kim, Jae-Sol Choi, Jae-Hun Jo, Jaewan Joe, Young-Hum Cho, Eui-Jong Kim
Summary: Accurate analysis of building energy performance requires reliable measurement methods. This study used dynamic simulations to verify the accuracy and reproducibility of commonly used field measurement methods and found that the HFM and IRTi methods exhibited high accuracy and reproducibility in evaluating the thermal performance of building envelopes.
CASE STUDIES IN THERMAL ENGINEERING
(2023)
Article
Pediatrics
Balasankar Ganesan, Joanne Yip, Ameersing Luximon, Paul J. Gibbons, Alison Chivers, Suchita Kothe Balasankar, Raymond Kai-Yu Tong, Rifai Chai, Adel Al-Jumaily
Summary: The study aimed to explore foot skin temperature changes in conservative treatment of clubfoot deformity. Results showed significant temperature changes in some regions of the foot after casting intervention.
FRONTIERS IN PEDIATRICS
(2021)
Article
Optics
Liu-Ya Chen, Yi-Ning Zhao, Lin-Shan Chen, Chong Wang, Cheng Ren, De-Zhong Cao
Summary: In this letter, a scheme of color ghost imaging is proposed to reduce the impact of ambient noise on image quality. The measurement matrix is optimized with low-pass filters, and the patterns of random speckles are filtered using four different filters. By using the TSVD method, the pseudo-inverse matrix of the optimized measurement matrix is obtained and used for image reconstruction. The experimental results show that the image quality is greatly improved and the point spread functions are optimized after filtering the random speckles.
OPTICS AND LASER TECHNOLOGY
(2024)
Article
Instruments & Instrumentation
Agustin Salazar, Arantza Mendioroz, Jon Perez-Arbulu, Ernesto Marin
Summary: In laser-spot step-heating thermography, a laser beam is focused on the sample surface while the infrared video camera monitors the surface temperature rise. By analyzing the temperature profile at different time points after turning on the laser beam, the in-plane thermal diffusivity can be determined. This study shows that in thermal insulators, heat conduction to the surrounding gas, usually neglected in these experiments, plays a significant role in determining both thermal diffusivity and conductivity simultaneously.
INFRARED PHYSICS & TECHNOLOGY
(2023)
Article
Instruments & Instrumentation
Shawli Bardhan, Satyabrata Nath, Tathagata Debnath, Debotosh Bhattacharjee, Mrinal Kanti Bhowmik
Summary: This study focuses on the limited application of thermography for inflammatory joint disease diagnosis and aims to create a knee thermogram dataset using standardized protocols. The dataset, named Infrared Knee Joint Dataset, includes healthy and arthritis affected knee thermograms. The experimental results show high accuracy in classifying healthy and arthritis knee thermograms, as well as distinguishing different types of arthritis.
QUANTITATIVE INFRARED THERMOGRAPHY JOURNAL
(2022)
Article
Computer Science, Interdisciplinary Applications
Pawan Kumar Singh, Soumalya Kundu, Titir Adhikary, Ram Sarkar, Debotosh Bhattacharjee
Summary: This survey provides an overview of the various approaches proposed for Human Action Recognition (HAR) in the past decade, focusing mainly on the development of methods for unimodal HAR using concepts of machine learning and deep learning models. It also includes discussions on different feature extractors, majorly used video and still-image datasets, and offers insights into future work scope.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2022)
Article
Computer Science, Information Systems
Subhadeep Koley, Hiranmoy Roy, Soumyadip Dhar, Debotosh Bhattacharjee
Summary: This study introduces a new facial feature descriptor, FCLPPC, for high accuracy cross-modal face recognition using phase congruency features and cross lattice patterns. By fusing invariant phase congruency features and weighted alpha-blending, the recognition accuracy is improved.
INFORMATION SCIENCES
(2022)
Article
Instruments & Instrumentation
Usha Rani Gogoi, Mrinal Kanti Bhowmik, Gautam Majumdar
Summary: This paper proposes a novel approach for grading breast abnormalities using a morphology model of suspicious hyperthermic regions (MMSHRs). The method segments and analyzes the morphology of suspicious hyperthermic regions in breast thermograms to classify the thermograms according to their severity. The classification accuracy of the method is 91% and the area under the receiver operating characteristic curve is 0.9998.
QUANTITATIVE INFRARED THERMOGRAPHY JOURNAL
(2023)
Article
Computer Science, Information Systems
Anu Singha, Mrinal Kanti Bhowmik
Summary: This study proposes a deep learning model called AlexSegNet, based on the AlexNet model, for the nuclei segmentation of microscopic images. Experimental results show that the proposed model achieves high segmentation performance on datasets with different sample types, and it is expected to be applied clinically in the analysis of cancer diagnosis.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Engineering, Civil
Geet Sahu, Ayan Seal, Debotosh Bhattacharjee, Robert Frischer, Ondrej Krejcar
Summary: Visibility issues in intelligent transportation systems, particularly in bad weather conditions, have led to major accidents worldwide. The proposed dehazing method utilizes a parameter-adaptive dual-channel modified simplified pulse coupled neural network (PA-DC-MSPCNN) to remove haze from images. By cascading two models and utilizing a fusion technique, the proposed approach outperforms state-of-the-art methods in terms of qualitative and quantitative performances.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Anu Singha, Mrinal Kanti Bhowmik
Summary: Object detection in adversarial atmospheric attacks is challenging in computer vision. This research proposes a deep convolutional architecture to restore video frames in adverse weather conditions and improve object detection performance.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Asish Bera, Mita Nasipuri, Ondrej Krejcar, Debotosh Bhattacharjee
Summary: Human body-pose estimation is a complex problem in computer vision, and recent research has focused on sports, yoga, and dance postures for maintaining health conditions. Deep convolutional neural networks have shown significant improvement in solving human body-pose estimation problems. However, there is currently no benchmark public image dataset available for sports and dance postures classification. To address this, we have proposed two image datasets for sports and dance postures, and our deep model, SYD-Net, has achieved state-of-the-art accuracy on the Yoga-82 dataset.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Electrical & Electronic
Kaushiki Roy, Debapriya Banik, Gordon K. Chan, Ondrej Krejcar, Debotosh Bhattacharjee
Summary: Cancer cell segmentation is challenging due to the overlapping of tightly packed colonies. This study proposes an automated framework, 2pClPr, for the segmentation of cancer cells in fluorescence microscopy images.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Electrical & Electronic
Mohan Karnati, Ayan Seal, Debotosh Bhattacharjee, Anis Yazidi, Ondrej Krejcar
Summary: Emotion recognition is important in cognitive psychology research, but measuring emotions is challenging. Facial expression recognition (FER) approaches have been designed, but challenges increase when data transitions to real-world circumstances. Deep learning (DL) techniques have greatly improved FER systems, but problems such as overfitting and complications unrelated to expressions still exist. This study provides a comprehensive survey of DL-based FER methods, discussing different components and analyzing their performance, advantages, and limitations. It also explores relevant databases and discusses the current status and future directions of facial emotion recognition.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Proceedings Paper
Materials Science, Multidisciplinary
Shyam Kumar Bhattacharjee, S. A. Hussain, D. Bhattacharjee
Summary: This study investigates the micellar effect on the increased fluorescence efficiency of a fluores-cent dye in complex LB films. It was found that the organizational structure of dye molecules in the films varied depending on whether the films were prepared below or above the critical micellar concentration (CMC) of Cetyltrimethylammonium Bromide (CTAB) in the mixed Langmuir Trough solution. Various techniques including BAM, UV-Vis absorption, and Fluorescence Spectroscopy were employed to study the spectral characteristics of the complex films.
MATERIALS TODAY-PROCEEDINGS
(2022)
Article
Computer Science, Theory & Methods
Hiranmoy Roy, Debotosh Bhattacharjee, Ondrej Krejcar
Summary: Heterogeneous Face Recognition (HFR) is a challenging task due to significant intra-class variation caused by different image capturing sensors and image representation techniques. Conventional deep learning models face difficulties in addressing this problem, including limited data samples and inability to adapt to complex scenarios. This paper proposes a novel interpretable model based on continual learning shallow network, which effectively solves these issues.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2022)
Article
Computer Science, Artificial Intelligence
Geet Sahu, Ayan Seal, Debotosh Bhattacharjee, Mita Nasipuri, Peter Brida, Ondrej Krejcar
Summary: For the last two decades, image processing techniques have been widely used in computer vision applications. This study describes various traditional and deep learning techniques of image dehazing, aiming to provide an intuitive understanding of these techniques and improve the comprehension of the dehazing process.
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE
(2022)
Article
Engineering, Electrical & Electronic
Kaushiki Roy, Debapriya Banik, Debotosh Bhattacharjee, Ondrej Krejcar, Christian Kollmann
Summary: COVID-19, a global pandemic, has typical abnormal findings in chest CT images such as ground-glass opacities (GGOs) and consolidation. Manual annotation of these abnormalities is complex and time-consuming, so we developed a vision-based analysis framework for automated segmentation of lung abnormalities. Our deep learning framework, LwMLA-NET, outperforms other state-of-the-art deep learning frameworks in terms of segmentation performance and has acceptable generalization capability.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
