Article
Surgery
Thomas M. Ward, Daniel A. Hashimoto, Yutong Ban, Guy Rosman, Ozanan R. Meireles
Summary: The study found that an AI model can accurately identify the degree of gallbladder inflammation, which has an impact on the intra-operative course. The automated assessment system can be used for optimizing the workflow in the operating room and providing targeted feedback to surgeons and residents, accelerating the acquisition of operative skills.
SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES
(2022)
Review
Chemistry, Multidisciplinary
Mingfei Wu, Chen Li, Zehuan Yao
Summary: This article introduces the applications and challenges of deep active learning in computer vision tasks, and briefly introduces the classic theories and strategies of active learning.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Artificial Intelligence
Wenhao Xue, Yang Yang, Lei Li, Zhongling Huang, Xinggang Wang, Junwei Han, Dingwen Zhang
Summary: Segmenting the semantic regions of point clouds is crucial for understanding 3D scenes. Weakly supervised point cloud segmentation is desirable due to the time-consuming and costly nature of fully labelling point clouds. However, existing methods struggle with transferring semantic information due to limitations in classifier discriminative capability and the orderless and structurless nature of point cloud data.
CAAI TRANSACTIONS ON INTELLIGENCE TECHNOLOGY
(2023)
Article
Construction & Building Technology
Shuangyu Wei, Paige Wenbin Tien, Yupeng Wu, John Kaiser Calautit
Summary: Occupants' behavior and electrical equipment usage have a significant impact on building energy demand. This study proposes a real-time detection and recognition approach using deep learning and computer vision techniques to efficiently control building energy. Experimental results demonstrate high accuracy in equipment and occupancy detection, and a case study shows the influence of the approach on building energy demand. The results highlight the importance of monitoring real-time occupancy and electrical equipment usage and the advantages of using deep learning detection techniques to optimize building energy efficiency.
JOURNAL OF BUILDING ENGINEERING
(2022)
Review
Surgery
Roi Anteby, Nir Horesh, Shelly Soffer, Yaniv Zager, Yiftach Barash, Imri Amiel, Danny Rosin, Mordechai Gutman, Eyal Klang
Summary: The study evaluated the accuracy of deep learning networks in analyzing laparoscopic surgery videos, showing applications mainly in surgery or instrument recognition, phase recognition, and anatomy recognition. Deep learning holds potential in laparoscopic surgery, but is limited by methodologies.
SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES
(2021)
Article
Business
Adrian Micu, Alexandru Capatina, Dragos Sebastian Cristea, Dan Munteanu, Angela-Eliza Micu, Daniela Ancuta Sarpe
Summary: The article introduces a prototype of on-site customer profiling and hyper-personalization system based on artificial intelligence, using deep learning approach to collect customer data from stores, providing more business possibilities.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2022)
Article
Materials Science, Multidisciplinary
Steffen Brinckmann, Ruth Schwaiger
Summary: The Oliver-Pharr method is a traditional approach for determining a material's Young's modulus and hardness, but it poses challenges for hard and stiff materials. This study introduces a new method that utilizes automatic image recognition to accurately identify Young's modulus and hardness from nanoindentation, eliminating the need for separate calibrations and surface contact identification. Our approach is demonstrated and evaluated for challenging nanoindentation of hard and stiff materials like silicon.
JOURNAL OF MATERIALS RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Shibao Li, Zekun Jia, Yixuan Liu, Xuerong Cui, Jianhang Liu, Tingpei Huang, Jiuyun Xu
Summary: The DETR network eliminates hand-designed components by using the Transformer architecture. The ambiguity of the object query in the Transformer slows down the convergence of DETR. Existing works aim to reduce ambiguity by strengthening the relationship between the object query and position information, but considering only position information is not comprehensive. Our CLS-DETR method considers the influence of classification information on DETR convergence and achieves faster convergence by optimizing the generation of the object query. It demonstrates the ability of clear classification information to accelerate DETR convergence.
PATTERN RECOGNITION LETTERS
(2023)
Article
Computer Science, Artificial Intelligence
Ting-Hui Chiang, Yi-Chun Tseng, Yu-Chee Tseng
Summary: This paper proposes an encoder-decoder ConvLSTM model for retrieving incident videos that contain more spatial and temporal semantics. The model encodes videos into embeddings and compares their similarity based on the embeddings. Extensive evaluations demonstrate that the proposed model outperforms other methods in various video retrieval tasks.
PATTERN RECOGNITION
(2022)
Article
Engineering, Multidisciplinary
Yuequan Bao, Hui Li
Summary: The conventional vibration-based methods face challenges in accurately detecting structural damages, thus necessitating the development of novel diagnosis and prognosis methods based on various monitoring data.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2021)
Review
Biochemistry & Molecular Biology
David F. Steiner, Po-Hsuan Cameron Chen, Craig H. Mermel
Summary: Recent advances in artificial intelligence show great promise in improving the accuracy of medical diagnostics, especially in the field of digital pathology. However, there are significant challenges in translating these technologies into clinical practice despite the increasing number of publications on their performance in diagnostic applications.
BIOCHIMICA ET BIOPHYSICA ACTA-REVIEWS ON CANCER
(2021)
Article
Automation & Control Systems
Matthew R. Wilkinson, Bernardo Castro-Dominguez, Chick C. Wilson, Uriel Martinez-Hernandez
Summary: This study modifies a 3D printer to enable rapid and autonomous sample characterization in pharmaceutical particle analysis, using low-cost hardware and open-source software. The system overcomes the limitations of subjective labeling and limited data in machine learning models, and allows researchers without access to sophisticated automation platforms to generate larger datasets for data-driven models.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Review
Radiology, Nuclear Medicine & Medical Imaging
Germana de Queiroz Tavares Borges Mesquita, Walbert A. Vieira, Maria Tereza Campos Vidigal, Bruno Augusto Nassif Travencolo, Thiago Leite Beaini, Rubens Spin-Neto, Luiz Renato Paranhos, Rui Barbosa de Brito Junior
Summary: Using artificial intelligence for detecting cephalometric landmarks in digital imaging examinations has shown promising results, but there is a lack of consensus on accuracy and precision. A meta-analysis of selected studies revealed AI agreement rates of 79-90% compared to manual detection, with the lowest divergence observed for the menton cephalometric landmark. However, further research is needed to validate AI's strength and effectiveness in different samples.
JOURNAL OF DIGITAL IMAGING
(2023)
Review
Ophthalmology
Luis F. Nakayama, Lucas Z. Ribeiro, Robyn G. Dychiao, Yuslay F. Zamora, Caio V. S. Regatieri, Leo A. Celi, Paolo Silva, Lucia Sobrin, Rubens Belfort Jr
Summary: The use of artificial intelligence in uveitis studies has the potential to improve screening and diagnosis, but there is a lack of validation studies and publicly available data and codes.
SURVEY OF OPHTHALMOLOGY
(2023)
Review
Chemistry, Analytical
Andrew A. Gumbs, Vincent Grasso, Nicolas Bourdel, Roland Croner, Gaya Spolverato, Isabella Frigerio, Alfredo Illanes, Mohammad Abu Hilal, Adrian Park, Eyad Elyan
Summary: This review focuses on the advances and limitations of computer vision in surgery and discusses how it can contribute to achieving more autonomous actions. It also highlights the use of non-visual data in aiding robotic autonomy and addresses the current crisis regarding autonomy in surgical procedures.
Article
Materials Science, Coatings & Films
D. Chicot, H. Ageorges, M. Voda, G. Louis, M. A. Ben Dhia, C. C. Palacio, S. Kossman
SURFACE & COATINGS TECHNOLOGY
(2015)
Article
Materials Science, Multidisciplinary
Stephania Kossman, Thierry Coorevits, Alain Iost, Didier Chicot
JOURNAL OF MATERIALS RESEARCH
(2017)
Article
Materials Science, Multidisciplinary
M. Bentoumi, D. Bouzid, H. Benzaama, A. Mejias, S. Kossman, A. Montagne, A. Iost, D. Chicot
JOURNAL OF MATERIALS RESEARCH
(2017)
Article
Materials Science, Coatings & Films
S. Kossman, D. Chicot, X. Decoopman, A. Iost, A. van Gorp, E. Meillot, E. S. Puchi-Cabrera, Y. Y. Santana, M. H. Staia
JOURNAL OF THERMAL SPRAY TECHNOLOGY
(2014)
Article
Materials Science, Coatings & Films
L. B. Coelho, S. Kossman, A. Mejias, X. Noirfalise, A. Montagne, A. Van Gorp, M. Poorteman, M. -G. Olivier
SURFACE & COATINGS TECHNOLOGY
(2020)
Article
Materials Science, Coatings & Films
Thierry Coorevits, Alberto Mejias, Alex Montagne, Stephania Kossman, Alain Iost
SURFACE & COATINGS TECHNOLOGY
(2020)
Article
Engineering, Mechanical
Stephania Kossman, Leonardo B. Coelho, Alberto Mejias, Alex Montagne, Adrien Van Gorp, Thierry Coorevits, Matthieu Touzin, Marc Poorteman, M. -G. Olivier, Alain Iost, Mariana H. Staia