Review
Biochemical Research Methods
Sung-Wook Hwang, Junji Sugiyama
Summary: The advancements in computer vision and machine learning have revolutionized scientific disciplines and created a new research field in wood science known as computer vision-based wood identification. Research has reviewed mainstream studies using machine learning procedures to familiarize wood scientists with this area and help them choose appropriate techniques in wood science.
Review
Forestry
Jose Luis Silva, Rui Bordalo, Jose Pissarra, Paloma de Palacios
Summary: Wood identification is an important tool in various fields. Computer vision-based technology provides a fast and accurate method for wood identification, but its application in fields like cultural heritage is still limited.
Article
Forestry
Sung-Wook Hwang, Junji Sugiyama
Summary: This paper discusses image partitioning strategies that preserve spatial information of wood cross-sectional images, achieving better recognition performance than traditional methods. Radial partitioning is particularly effective for radial-porous species and can provide auxiliary correlation coefficients for multi-feature datasets. The contribution of image partitioning strategies is limited to species recognition and is not significant at the genus level.
JOURNAL OF WOOD SCIENCE
(2021)
Article
Surgery
R. B. den Boer, T. J. M. Jaspers, C. de Jongh, J. P. W. Pluim, F. van der Sommen, T. Boers, R. van Hillegersberg, M. A. J. M. Van Eijnatten, J. P. Ruurda
Summary: This study developed a deep learning algorithm to recognize anatomical structures in video frames from robot-assisted minimally invasive esophagectomy (RAMIE) procedures. It shows potential for clinical application and further prospective clinical studies are needed to assess its effectiveness.
SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES
(2023)
Article
Robotics
Ji-il Park, Yeongseok Lee, Eungyo Suh, Hyunyong Jeon, Kuk-Jin Yoon, Kyung-soo Kim
Summary: This study improved the accuracy of optical flow estimation by optimizing fundamental parameters such as the number of pyramids, filters, window size, and GNC step number, instead of using deep learning methods.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Computer Science, Artificial Intelligence
Muhammad Hassan Khan, Muhammad Shahid Farid, Marcin Grzegorzek
Summary: Vision-based person identification using gait is a challenging task in computer vision and machine learning. It is non-invasive and can be performed at a distance without active collaboration. However, traditional gait recognition methods are sensitive to variations in silhouette shapes, limiting their efficacy.
INFORMATION FUSION
(2023)
Article
Computer Science, Artificial Intelligence
XinChao Meng, Si Si
Summary: In this paper, an active contour model based on a hybrid signed pressure force function that fuses global and local image information is proposed for segmenting noisy and multi-target images. A local signed pressure force function is defined using the local area information of the image and combined with the existing global grey density function to construct a new function. The selective binary and Gaussian filtering regularized level set are modified using the newly defined function. Extensive experiments and comparisons demonstrate the robustness of the proposed method to noise and its high accuracy in handling noisy and multi-target images.
IET IMAGE PROCESSING
(2023)
Article
Engineering, Electrical & Electronic
Attila Fejer, Zoltan Nagy, Jenny Benois-Pineau, Peter Szolgay, Aymar de Rugy, Jean-Philippe Domenger
Summary: This paper discusses the FPGA implementation of the SIFT algorithm and its application in vision-guided hybrid neuro-prostheses for upper limbs replacement. By optimizing the algorithm for FPGA and comparing it with other hardware or hybrid implementations, it is found that the proposed solution has lower power consumption and better computational speed, allowing for real-time processing of medium-sized images.
INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS
(2021)
Article
Engineering, Marine
Manzoor Ahmed Hashmani, Muhammad Umair
Summary: This article proposes a new sea image dataset that encompasses various geographical, seasonal, and maritime features, and is used for testing and evaluating computer vision-based SHL detection methods.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2022)
Article
Computer Science, Information Systems
Fengcai Huo, Ang Li, Weijian Ren, Di Wang, Tao Yu
Summary: In the industry, the traditional method of manually recording and analyzing data from pointer meters in industrial production has low efficiency and leads to inaccuracies. To solve this problem, a new method based on computer vision technology for pointer detection and indicator recognition is proposed, which improves accuracy and efficiency through image processing and feature extraction.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Xunru Liang, Jianfeng Liang, Tao Yin, Xiaoyu Tang
Summary: This paper introduces a lightweight network based on improved MobileNetV3 to address the shortcomings of existing models in facial expression recognition, such as excessive parameters, large model sizes, and high computational costs. The network adjusts the channels and incorporates a coordinate attention mechanism to enhance attention with fewer parameters and lower computing cost. Additionally, a complementary pooling structure is designed to improve the coordinate attention mechanism and assist in extracting salient features. The network achieves high accuracy on public datasets with minimal FLOPs, parameters, and memory storage size.
IET IMAGE PROCESSING
(2023)
Review
Surgery
R. B. den Boer, C. de Jongh, W. T. E. Huijbers, T. J. M. Jaspers, J. P. W. Pluim, R. van Hillegersberg, M. Van Eijnatten, J. P. Ruurda
Summary: This study provides a comprehensive overview of the accuracy of anatomy recognition algorithms in intrathoracic and abdominal surgery. The results show that the accuracy of these algorithms varies substantially, with higher accuracy achieved through training on larger datasets annotated by experts and focusing on less-complex anatomy. The study highlights the emerging field of computer-aided intraoperative anatomy recognition and emphasizes the need for larger datasets and methodological guidelines to improve accuracy and clinical applicability in future research.
SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES
(2022)
Article
Chemistry, Analytical
Rich C. Lee, Ing-Yi Chen
Summary: Public aquariums and similar institutions use video for monitoring aquatic organisms, requiring autoencoders to reduce file size. Simplifying the autoencoder model design is ideal for fulfilling the practical needs of aquariums.
Article
Construction & Building Technology
Gozdenur Demir, Asli Cekmis, Vahit Bugra Yesilkaynak, Gozde Unal
Summary: This research aims to utilize artificial intelligence technologies to recognize and classify design principles across different domains, including artwork, professional photos, and facade pictures of contemporary buildings. By learning from original designs and capturing shared underlying patterns, the proposed model aims to provide an objective aesthetic evaluation.
AUTOMATION IN CONSTRUCTION
(2021)
Review
Computer Science, Theory & Methods
Gilberto Astolfi, Fabio Prestes Cesar Rezende, Joao Vitor De Andrade Porto, Edson Takashi Matsubara, Hemerson Pistori
Summary: This article provides an overview of the use of syntactic methods in computer vision tasks. A systematic literature review was conducted to survey relevant studies, with 71 papers selected for analysis. The results indicate that syntactic methods are often used as a high-level structure to handle relationships between objects or actions.
ACM COMPUTING SURVEYS
(2022)
Article
Chemistry, Multidisciplinary
Tom Willhammar, Kazuho Daicho, Duncan N. Johnstone, Kayoko Kobayashi, Yingxin Liu, Paul A. Midgley, Lennart Bergstrom, Tsuguyuki Saito
Summary: This study used scanning electron diffraction and atomic force microscopy to directly measure the local ordering of polysaccharide chains and twisting structures in cellulose nanofibers, shedding new light on the properties of single-cellulose fibrils. This understanding has important implications for optimizing cellulose extraction and separation processes in dense assemblies.
Article
Forestry
Sung-Wook Hwang, Junji Sugiyama
Summary: This paper discusses image partitioning strategies that preserve spatial information of wood cross-sectional images, achieving better recognition performance than traditional methods. Radial partitioning is particularly effective for radial-porous species and can provide auxiliary correlation coefficients for multi-feature datasets. The contribution of image partitioning strategies is limited to species recognition and is not significant at the genus level.
JOURNAL OF WOOD SCIENCE
(2021)
Article
Forestry
Sung-Wook Hwang, Hiroshi Isoda, Takafumi Nakagawa, Junji Sugiyama
Summary: This study investigated the flexural anisotropy of wood and discovered different deformation mechanisms of various wood grain patterns. Rift-sawn softwood demonstrated excellent flexibility, largely due to the tapered shape of the tracheid walls.
JOURNAL OF WOOD SCIENCE
(2021)
Review
Biochemical Research Methods
Sung-Wook Hwang, Junji Sugiyama
Summary: The advancements in computer vision and machine learning have revolutionized scientific disciplines and created a new research field in wood science known as computer vision-based wood identification. Research has reviewed mainstream studies using machine learning procedures to familiarize wood scientists with this area and help them choose appropriate techniques in wood science.
Article
Chemistry, Multidisciplinary
Kazuho Daicho, Kayoko Kobayashi, Shuji Fujisawa, Tsuguyuki Saito
Summary: By enhancing inter-crystallite interactions, grain boundaries within a crystalline nanofiber aggregate were crystallized, allowing for the fusion of multiple crystallites into single fusion crystals, thus improving thermal energy transfer efficiency.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
(2021)
Article
Materials Science, Paper & Wood
Shingo Kiyoto, Junji Sugiyama
Summary: The study revealed that the outer layer and inner material of birch cork mainly consist of suberin, while the inner layer and compound middle lamella are composed of lignin, cellulose, and other polysaccharides. Cellulose microfibrils in the inner layer bear tensile loads. Additionally, in the wet state, water and cellulose transfer tensile stress.
Article
Multidisciplinary Sciences
Sung-Wook Hwang, Un Taek Hwang, Kyeyoung Jo, Taekyeong Lee, Jinseok Park, Jong-Chan Kim, Hyo Won Kwak, In-Gyu Choi, Hwanmyeong Yeo
Summary: This study established prediction models for the non-destructive evaluation of lignin-derived hydrochars' carbonization characteristics using near-infrared spectra, accurately predicting carbon content, oxygen/carbon, and hydrogen/carbon ratios with high coefficients of determination and low root mean square errors. The models showed better prediction performance compared to ordinary least squares regression models.
SCIENTIFIC REPORTS
(2021)
Article
Chemistry, Applied
YunJin Kim, Junsik Bang, Jungkyu Kim, June-Ho Choi, Sung-Wook Hwang, Hwanmyeong Yeo, In-Gyu Choi, Hyoung-Joon Jin, Hyo Won Kwak
Summary: Nanocellulose is gaining interest as an eco-friendly water treatment material due to its large specific surface area and abundant hydroxyl functional groups, but its dispersion state hampers practical usage. A regenerated cellulose hydrogel with cationic functional groups was developed to address the low performance of nanocellulose in removing anionic pollutants. The PEI surface cationization process improved mechanical rigidity and showed excellent Cr(VI) removal capacity, maintaining high efficiency after multiple reuses.
CARBOHYDRATE POLYMERS
(2022)
Article
Materials Science, Paper & Wood
Ryo Nagamine, Kayoko Kobayashi, Ryosuke Kusumi, Masahisa Wada
Summary: This study is the first to compare the biodegradability of cellulose fibers with different structures in natural waters. The results showed that cellulose fibers are easily degraded into fine fragments, but it is difficult to completely decompose them into water and carbon dioxide. Additionally, the degradation behavior of cellulose fibers was influenced by different water environments.
Article
Materials Science, Paper & Wood
Yangyang Zhang, Qinfeng He, Kayoko Kobayashi, Ryosuke Kusumi, Masahisa Wada
Summary: Hydrogels prepared from enzymatically synthesized dextran and carboxymethyl cellulose showed different properties depending on the CMC and dextran content. They exhibited excellent adsorption capabilities for heavy metal ions and dyes, and demonstrated potential for multiple reuses.
Article
Forestry
Hairi Cipta, Kayoko Kobayashi, Shuoye Chen, Junji Sugiyama
Summary: This study analyzed the wood grain of Cinnamomum camphora using X-ray computed tomography, PIV, and 2D-FFT. The findings revealed periodic changes in wood grain orientation, with a wide range of grain angle variation and minor deviation in vessel inclining direction.
JOURNAL OF WOOD SCIENCE
(2022)
Article
Chemistry, Physical
Tomoki Ito, Kazuho Daicho, Shuji Fujisawa, Tsuguyuki Saito, Kayoko Kobayashi
Summary: Atomic-scale dent structures were found on the surfaces of cellulose nanofibers, constituting a significant portion of the total length and leading to kinking and fragmentation of the nanofibers.
NANOSCALE HORIZONS
(2022)
Article
Forestry
Sung-Wook Hwang, Taekyeong Lee, Hyunbin Kim, Hyunwoo Chung, Jong Gyu Choi, Hwanmyeong Yeo
Summary: This paper discusses feature-based techniques for wood knot classification, comparing the performance of texture and local feature descriptors and determining that texture descriptors are more suitable for wood knot classification. Additionally, it confirms that artificial neural network models are better suited for wood knot classification tasks.
