Versatility Evaluation of Landslide Risk with Window Sizes and Sampling Techniques Based on Deep Learning by Fudong Ren, Koichi Isobe

“…Unlike conventional methods that often require manual feature selection and engineering, CNNs automate feature extraction, enabling a more nuanced understanding of complex patterns. …”
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Landscapes of Trade by Merten Nefs

“…These include the seemingly ubiquitous growth pattern of DCs in the Netherlands, the dominant and increasingly challenged policy narrative of the Netherlands as a ‘gateway to Europe’, and the public-private actor network that appears to fall short of adequate DC planning and development. …”
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Deep Learning Based Breast Cancer Detection Using Decision Fusion by Doğu Manalı, Hasan Demirel, Alaa Eleyan

“…First, SVM distinguishes between different tumor types using local binary pattern (LBP) features. Second, a pre-trained CNN extracts features, and SVM identifies potential tumors. …”
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Prediction of crystalline structure evolution during solidification of aluminum at different cooling rates using a hybrid neural network model by Rafi B. Dastagir, Shorup Chanda, Farsia K. Chowdhury, Shahereen Chowdhury, K. Arafat Rahman

“…By combining the temporal pattern descriptors of LSTMs with the feature extraction potential of convolutional neural networks (CNN), the hybrid Conv1D-LSTM model achieves higher accuracy in predicting crystal structural evolution curves, in contrast to the performance of standalone LSTM and CNN models. …”
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Tipping the balance: robustness of tip cell selection, migration and fusion in angiogenesis. by Katie Bentley, Giovanni Mariggi, Holger Gerhardt, Holger Gerhardt, Paul A Bates

“…A novel filopodia-adhesion driven migration mechanism is presented and validated against in vivo data. Due to the unique feature of ongoing lateral inhibition, 'stabilised' tip/stalk cell patterns show sensitivity to the formation of new cell-cell junctions during fusion: we predict cell fates can reverse. …”
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Employing the concept of stacking ensemble learning to generate deep dream images using multiple CNN variants by Lafta Alkhazraji, Ayad R. Abbas, Abeer S. Jamil, Zahraa Saddi Kadhim, Wissam Alkhazraji, Sabah Abdulazeez Jebur, Bassam Noori Shaker, Mohammed Abdallazez Mohammed, Mohanad A. Mohammed, Basim Mohammed Al-Araji, Abdulkareem Z. Mohmmed, Wasiq Khan, Bilal Khan, Abir Jaafar Hussain

“…Performance of the proposed model was evaluated across three octaves to amplify the maximum possible patterns and features of the base image. The resulting dream-like images contain shapes that reflect elements from the ImageNet dataset on which the above pre-trained models were trained. …”
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THE USE OF THE ELEMENTS OF MORPHOECOLOGICAL ADAPTATIONS OF ORGANISMS TO THE ENVIRONMENT UNDER PALEOGEOGRAPHIC RECONSTRUCTIONS OF BIOTAS OF TETIYSKY DESERT-STEPPE REGION (BUILDING S... by G. M. Abdurakhmanov, I. V. Shokhin, A. A. Teymurov, A. G. Abdurakhmanov, A. A. Gadzhiev, M. G. Daudova, M. Z. Magomedova, Yu. Yu. Ivanushenko

“…The structure of the feet of Tenebrionidae is closely related to their living conditions and patterns of behavior. Convergence in the structure of the feet of phylogenetically distant species is the result of a match in their evolutionary development of the living conditions and behavioral characteristics. …”
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Characterizing a complex buildup in the Pearl River Mouth Basin of the northern South China Sea: an interplay of carbonates and igneous rocks by Beichen Chen, Leyi Xu, Baojun Liu, Lili Zhang, Dong Xiao, Ya Gao, Ya Gao, Feng Wu, Xueqi Yang, Yaming Zou, Yongkun Ma, Yinglin Zhang

“…By analyzing the lithofacies of the carbonates and igneous rocks, the morphological features and spatial distribution patterns corresponding to these sedimentary and volcanic facies were identified. …”
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SOH Estimation Method for Lithium-Ion Batteries Using Partial Discharge Curves Based on CGKAN by Shengfeng He, Wenhu Qin, Zhonghua Yun, Chao Wu, Chongbin Sun

“…Finally, multiple experiments under different conditions are conducted, and the results demonstrate that the proposed CGKAN method, by integrating the individual advantages of 1D-CNN, BiGRU, and KAN, efficiently captures complex nonlinear patterns in battery health features and maintains stable performance across various operating conditions.…”
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Deep learning for rice leaf disease detection: A systematic literature review on emerging trends, methodologies and techniques by Chinna Gopi Simhadri, Hari Kishan Kondaveeti, Valli Kumari Vatsavayi, Alakananda Mitra, Preethi Ananthachari

“…Image processing techniques are used to extract features from diseased leaf images, such as the color, texture, vein patterns, and shape of lesions. …”
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Using the antibody-antigen binding interface to train image-based deep neural networks for antibody-epitope classification. by Daniel R Ripoll, Sidhartha Chaudhury, Anders Wallqvist

“…We hypothesized that Abs recognizing the same part of an antigen share a limited set of features at the binding interface, and that the binding site regions of these Abs share share common structure and physicochemical property patterns that can serve as a "fingerprint" to recognize uncharacterized Abs. …”
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MetaTrans-FSTSF: A Transformer-Based Meta-Learning Framework for Few-Shot Time Series Forecasting in Flood Prediction by Jiange Jiang, Chen Chen, Anna Lackinger, Huimin Li, Wan Li, Qingqi Pei, Schahram Dustdar

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Frequency and Determinants of Flare and Persistently Active Disease in a Large Multinational Prospective Lupus Cohort by Yanjie Hao, Dylan Hansen, Worawit Louthrenoo, Yi‐Hsing Chen, Jiacai Cho, Aisha Lateef, Laniyati Hamijoyo, Shue Fen Luo, Yeong‐Jian Wu, Sandra Navarra, Leonid Zamora, Zhanguo Li, Sargunan Sockalingam, Yasuhiro Katsumata, Masayoshi Harigai, Lanlan Ji, Zhuoli Zhang, Madelynn Chan, Jun Kikuchi, Tsutomu Takeuchi, Sang‐Cheol Bae, Fiona Goldblatt, Sean O'Neill, Kristine (Pek Ling) Ng, B. M. D. B. Basnayake, Nicola Tugnet, Naoaki Ohkubo, Yoshiya Tanaka, Cherica Tee, Michael Tee, C. S. Lau, Ning Li, Vera Golder, Alberta Hoi, Rangi Kandane‐Rathnayake, Eric Morand, Shereen Oon, Mandana Nikpour, for the Asia Pacific Lupus Collaboration

“…Conclusion Both flare and PAD are common disease activity patterns in SLE; both predict organ damage accrual but differ in disease features and predictive factors. …”
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Révision de l’espèce Homo erectus (Dubois, 1893) by Valéry Zeitoun

“…The reconstruction of this evolutionary pattern should be matched with other data (dating, biogeography) to allow to reconstruct a real evolutionary synopsis.According to several authors (Stringer, 1984; Hublin, 1986; Kennedy, 1991; Brauer and Mbua, 1992) the existence of autapomorphic features for Homo erectus is not proved. …”
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Integration of biomimetic organoid-on-chip and 2D models advances the mechanistic Understanding of STEAP3-mediated regulation in intestinal viral infection by Yi-Wen Chen, Huan-Jung Chiang, Kuan-Ting Liu, Chun-Wei Kao, Shan-Ren Xie, Chao-Ming Su, Yu-Yin Shih

“…These systems often fail to capture key features such as spatial cell–cell interactions, tissue-specific heterogeneity, and microenvironmental complexity that govern virus–host dynamics in vivo. …”
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Radiology of viral pneumonia by A. A. Speranskaia, L. N. Novikova, O. P. Baranova, M. A. Vasilieva

“…X-ray patterns were identical to the previous epidemic in 10 patients. …”
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The brain-gut microbiota network (BGMN) is correlated with symptom severity and neurocognition in patients with schizophrenia by Runlin Peng, Wei Wang, Liqin Liang, Rui Han, Yi Li, Haiyuan Wang, Yuran Wang, Wenhao Li, Shixuan Feng, Jing Zhou, Yuanyuan Huang, Fengchun Wu, Kai Wu

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Spatial heterogeneity of cultural ecosystem services in grand canal rural heritage sites: A community gradient framework using participatory mapping by Xin Jiang, Xi Chen, Qinghai Zhang, Yutao Li, Mingrui Wang, Yongjun Li, Xing Xiong, Xiaoning Wu, Xin Li, Yujia Zhong, Yong Lu

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A Comprehensive Framework for Adaptive Electric Vehicle Charging Station Siting and Sizing Based on Transferable Spatio-Temporal Demand Prediction by Yutong Peng, Liqi Ye, Wenrui Ouyang, Qi Xi, Jing Wang, Xiaolin Wang

“…Under the global trend of promoting green development, the electric vehicle (EV) industry has entered a period of rapid growth. …”
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Applications and prospects of artificial intelligence in the auxiliary diagnosis of nail diseases by HE Mengwen, MAI Sien, MA Han

“…For melanonychia, relevant AI models typically identify disease patterns through segmentation and/or classification approaches. …”
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