Multi-modal expert system for automated durian ripeness classification using deep learning by Santi Sukkasem, Watchareewan Jitsakul, Phayung Meesad

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High-Precision Qiantang River Water Body Recognition Based on Remote Sensing Image by Hongcui Wang, Yihong Zheng, Ouxiang Chen

“…., are applied, Currently there are few works on the water body identification of Qiantang River, Here, one major challenge for high-precision Qiantang water body recognition is the real complex water body features and complicated geological environment, They are the dense distribution of small water bodies in the Qiantang River Basin, large differences in water body nutrition, and the high complexity of surface environments such as mountains and plains, We investigated two traditional and several deep learning methods and found that WatNet was the most effective model for Qiantang River, This model adopts the structure based on encoder-decoder convolutional network, It uses MobileNetV2 as the encoder, which makes it extract more water feature information while being lightweight and uses ASPP module to capture global multi-scale features in deep layers, Experimental results show that the MIoU and OA (Overall Accuracy) can reach 0. 97 and 0. 99 respectively.…”
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A transformation uncertainty and multi-scale contrastive learning-based semi-supervised segmentation method for oral cavity-derived cancer by Ran Wang, Chengqi Lyu, Lvfeng Yu

“…Additionally, a boundary-aware enhanced U-Net is proposed to capture boundary information and improve segmentation accuracy.ResultsExperimental results on the OCDC dataset demonstrate that our method outperforms both fully supervised and existing semi-supervised approaches, achieving superior segmentation performance.ConclusionsOur semi-supervised method, integrating transformation uncertainty, multi-scale contrastive learning, and a boundary-aware enhanced U-Net, effectively addresses data scarcity and improves segmentation accuracy. …”
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Improving trend prediction of agricultural futures price using image encoding and attention mechanisms by Dabin Zhang, Huiqiang Xie, Huanling Hu, Zehui Yu

“…Furthermore, we enhance the model’s feature extraction capabilities by fusing encoded image features with original numerical features, minimizing information loss during data transformation. Experimental results across two datasets demonstrate that ImgEnc-AttNet significantly outperforms benchmark models in both prediction accuracy and robustness.…”
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Community structure of Neuroptera (Insecta) in a Mexican lime orchard in Colima, Mexico by Mariza Araceli Sarmiento-Cordero, Beatriz Rodríguez-Vélez, Francisco Martín Huerta-Martínez, Claudia Aurora Uribe-Mú, Atilano Contreras-Ramos

“…Sampling was carried out monthly using 5 collecting techniques: Malaise trap, sweeping net, aerial net, yellow pan traps, and canopy fogging. …”
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Behavioural and physiological effects of finely balanced decision-making in chickens. by Anna C Davies, Christine J Nicol, Mia E Persson, Andrew N Radford

“…An unbalanced decision was one in which the two options were of unequal net value (1 (Q1) vs. 6 (Q6) pieces of sweetcorn with no cost associated with either option); a finely balanced decision was one in which the options were of equal net value (i.e. hens were "indifferent" to both options). …”
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Deep Learning Utilization for In-Line Monitoring of an Additive Co-Extrusion Process Based on Evaluation of Laser Profiler Data by Valentin Lang, Christian Thomas Ernst Herrmann, Mirco Fuchs, Steffen Ihlenfeldt

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Different orthology inference algorithms generate similar predicted orthogroups among Brassicaceae species by Irene T. Liao, Karen E. Sears, Lena C. Hileman, Lachezar A. Nikolov

“…Results produced using OrthNet were generally outliers but could still provide detailed information about gene colinearity. …”
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Evaluation of the details and importance of lymphatic, microvascular, and perineural invasion in patients with non-functioning pancreatic neuroendocrine neoplasms based on tumor si... by Wataru Izumo, Hiromichi Kawaida, Ryo Saito, Yuki Nakata, Hidetake Amemiya, Suguru Maruyama, Koichi Takiguchi, Katsutoshi Shoda, Kensuke Shiraishi, Shinji Furuya, Yoshihiko Kawaguchi, Kunio Mochizuki, Tetsuo Kondo, Daisuke Ichikawa

“…Patients with neuroendocrine tumor (NET) G1 had significantly fewer occurrences of lymphatic, microvascular, and perineural invasion than those with NET G2 (10%, 15%, and 7% vs. 40%, 55%, and 35%; all P < 0.05.). …”
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Prediction of bone oligometastases in breast cancer using models based on deep learning radiomics of PET/CT imaging by Guoxiu Lu, Guoxiu Lu, Ronghui Tian, Wei Yang, Jiayi Zhao, Wenjing Chen, Zijie Xiang, Shanhu Hao, Guoxu Zhang

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A Chinese prospective cohort research developed and validated a risk prediction model for patients with cervical cancer by Li Yuan, Baogang Wen, Xiuying Li, Haike Lei, Dongling Zou, Qi Zhou

“…Additionally, the predictive model’s capacity for outcome prediction and its net benefit were evaluated using the Net Reclassification Index (NRI) and Decision Curve Analysis (DCA) curves. …”
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The Importance of Community-Based and Community-Partnered COVID-19 Testing for Reducing Disparities Among African American Populations by Chavon Hamilton-Burgess, Jannette Berkley-Patton, Jenifer Allsworth, Carole Bowe Thompson, Frank E. Thompson, Tacia Burgin, Eric D. Williams, Kathryn P. Derose

“…Public health departments and other safety-net providers across the United States have partnered with community-based organizations to address barriers to COVID-19 testing in disproportionately impacted communities. …”
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In-depth exploration and application of fracturing construction curves in fractured tight sandstone reservoirs of the Tarim Basin by Mingjin Cai, Haofei Zhang, Haofei Zhang, Jianli Qiang, Zhimin Wang, Guoqing Yin, Chaoqun Xie, Chaoqun Xie, Keyou Chen, Keyou Chen, Haojiang Xi, Haojiang Xi

“…To thoroughly explore the information contained in the construction curves and accurately characterize hydraulic fracturing parameters, this study proposes a dynamic bottomhole net pressure calculation method based on real-time fracturing construction data, allowing for more precise correction of the bottomhole net pressure. …”
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METODOLOGINIAI INFORMACIJOS VISUOMENĖS STUDIJŲ PROFILIAI: VYNAS JAUNAS, VYNMAIŠIAI SENI? by Marius Povilas Povilas Šaulauskas

“…METHODOLOGICAL PROFILES OF THE INFORMATION SOCIETY STUDIES: NEW WINE, OLD WINESKINS? …”
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C-Band 200 Gbit&#x002F;s&#x002F;&#x03BB; PS-PAM-8 Transmission Over 2-km SSMF for Optical Interconnections by Xuancheng Huo, Meng Xiang, Gai Zhou, Jilong Li, Jianping Li, Yuwen Qin, Songnian Fu

“…After 2-km standard single-mode fiber (SSMF) transmission, the net data rate can be increased from 197 Gbit&#x002F;s of uniformly distributed PAM-8 to 212 Gbit&#x002F;s by the use of Optimized PMB-PAM-8, which can satisfy the requirement of 200G per lane optical interconnections.…”
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METODOLOGINIAI INFORMACIJOS VISUOMENĖS STUDIJŲ PROFILIAI: VYNAS JAUNAS, VYNMAIŠIAI SENI? by Marius Povilas Povilas Šaulauskas

“…METHODOLOGICAL PROFILES OF THE INFORMATION SOCIETY STUDIES: NEW WINE, OLD WINESKINS? …”
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METODOLOGINIAI INFORMACIJOS VISUOMENĖS STUDIJŲ PROFILIAI: VYNAS JAUNAS, VYNMAIŠIAI SENI? by Marius Povilas Povilas Šaulauskas

“…METHODOLOGICAL PROFILES OF THE INFORMATION SOCIETY STUDIES: NEW WINE, OLD WINESKINS? …”
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METODOLOGINIAI INFORMACIJOS VISUOMENĖS STUDIJŲ PROFILIAI: VYNAS JAUNAS, VYNMAIŠIAI SENI? by Marius Povilas Povilas Šaulauskas

“…METHODOLOGICAL PROFILES OF THE INFORMATION SOCIETY STUDIES: NEW WINE, OLD WINESKINS? …”
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Deep-Learning-Based Computer-Aided Grading of Cervical Spinal Stenosis from MR Images: Accuracy and Clinical Alignment by Zhiling Wang, Xinquan Chen, Bin Liu, Jinjin Hai, Kai Qiao, Zhen Yuan, Lianjun Yang, Bin Yan, Zhihai Su, Hai Lu

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Finger Knuckle Print classification: Leveraging vision Mamba for low complexity and high accuracy by Chiron Bang, Ali Salem Altaher, Ahmed Altaher, Hawraa Moamin, Thamer Alshammari, Basmh Alkanjr, Hasan Altaher, Mohammed G. Al-Jassani, Hanqi Zhuang

“…ViM achieved an impressive accuracy of 99.1%, outperforming other models such as AlexNet (96.2%), SCNN (98.3%), and EfficientNet (98.0%), highlighting its superior capability in FKP classification. …”
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