Advanced leukocyte classification using attention mechanisms and dual channel U-Net architecture by Gauri Kalnoor, Vijayalaxmi Kadrolli

“…Different conventional leukocyte analysis approaches often face several problems like inaccuracies, demanding the need for sophisticated approaches to improve diagnostic precision. …”
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Comparative Analysis of Fine-Tuning I3D and SlowFast Networks for Action Recognition in Surveillance Videos by T. Gopalakrishnan, Naynika Wason, Raguru Jaya Krishna, Vamshi Krishna B, N. Krishnaraj

“…In this paper, we solve the problems of low data and resource availability in surveillance datasets by employing transfer learning and fine-tuning the Inflated 3D CNN model and the SlowFast Network model to automatically extract features from surveillance videos in the SPHAR dataset for classification into respective action classes. …”
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Aircraft Sensor Fault Diagnosis Based on GraphSage and Attention Mechanism by Zhongzhi Li, Jinyi Ma, Rong Fan, Yunmei Zhao, Jianliang Ai, Yiqun Dong

“…Traditional deep learning-based fault diagnosis methods often face challenges, such as limited data representation and insufficient feature extraction. To address these problems, this paper proposes an enhanced GraphSage-based fault diagnosis method that incorporates attention mechanisms. …”
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Risk Environments of Permanent Supportive Housing for Formerly Incarcerated People with Serious Mental Illnesses: A Protocol for a Novel Mixed Methods Feasibility Study by Liat S. Kriegel, Benjamin F. Henwood, Michael G. McDonell, Ofer Amram, Chyrell Bellamy, Susan Collins, Mark Salzer

“…Participatory mapping will be geocoded and sites identified as places of importance, frequent participation, and belonging will be evaluated in relation to objective features of spaces to develop a community resilience index. …”
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Fulfillment of social obligations during the Soviet period of the Russian state and law development by R.R. Dolotina

“…The review of the key studies on social security revealed certain problems related to the formation of social obligations and their fulfillment. …”
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Object Detection Method of Inland Vessel Based on Improved YOLO by Yaoqi Wang, Jiasheng Song, Yichun Wang, Rongjie Wang, Hongyu Chen

“…Firstly, the CAA attention module is introduced into the Backbone network, and the C2f_CAA module is constructed at the same time to enhance the features of the central region and improve the understanding ability of complex scenes. …”
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Mechanism of self-induced haudralic fracturing in undeveloped formations and assessment of its impact on field development on the example of the Priobskoye field by А. I. Islamov, S. D. Esaulkov

“…A crack breakthrough, in turn, leads to problems associated with unproductive injection.Aim. …”
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Expression Recognition Algorithm of Deeply Separable Residual Network under Joint Loss by LI Jingyu, CHENG Weiyue, LIN Kezheng, MIAO Zhuang, LI Ao

“… In order to enhance the feature extraction ability of neural network and further improve the accuracy of facial expression recognition, this paper proposes a deep separable residual network model under joint loss DSResNet-Jloss.This network is a lightweight network model based on deep separable convolution and residual learning methods.The method of channel-by-channel convolution and point-by-point convolution is used to replace the conventional convolution operation, which solves the problems of traditional convolutional neural network with large parameter redundancy, long training time, slow convergence, and easy overfitting.And add residual unit to the network, use shortcut connection, through identity mapping, to solve the problem of gradient explosion or attenuation caused by too many layers of the network model.A joint loss function is proposed, which fully combines the advantages of cross-entropy loss, center loss and contrast loss to reduce the intra-class distance of expression features and increase the inter-class distance.Experiments show that the model has achieved good results on the two public data sets of FERPlus and RAF-DB, showing good generalization ability and robustness.…”
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Dynamic Grouping With Multi-Manifold Attention for Multi-View 3D Object Reconstruction by Georgios Kalitsios, Dimitrios Konstantinidis, Petros Daras, Kosmas Dimitropoulos

“…In a multi-view 3D reconstruction problem, the task is to infer the 3D shape of an object from various images taken from different viewpoints. …”
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Secure data transmission in geographically distributed information systems in ophthalmology based on domestic equipment by I.A. Ushakov, R.I. Dementiev, D.Ya. Derzhko

“…Purpose. To evaluate the features of the transition to Eltex equipment when building a DMVPN in geographically distributed information systems in ophthalmology. …”
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Requirements for the mass and heating of blanks selection in automated ring-rolling complexes by V. E. Antonyuk, S. G. Sandomirski, V. V. Yavorsky, N. P. Timoshenko, A. V. Budzinskaya

“…The conditions for choosing a billet mass for the manufacture of an ring part on an automated ring-rolling complex, the features of heating the billets in the conditions of an automated line and heat treatment of manufactured parts are considered. …”
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An Ensemble Classification Method Based on a Stacking Strategy for Ship Type Classification with AIS Data by Lei Deng, Shichen Yang, Limin Jia, Danyang Geng

“…Traditional ship type classification methods with AIS data are often plagued by problems such as data imbalance, insufficient feature extraction, reliance on single-model approaches, or unscientific model combination methods, which reduce the accuracy of classification. …”
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Pulmonary Nodules Detection Algorithm Combining Multi-view and Attention Mechanism by LIU Yu-bo, LIU Guo-zhu, SHI Cao, XU Can-hui

“…Then, the multi-view input method was used to ensure that the spatial features of nodules was obtained. The sections from 9 angles in three-dimensional space, including sagittal plane, coronal plane and horizontal plane, were input into the network together.The ViT network was used as a feature extractor and combined with the feature pyramid network to achieve the classification of nodules, and we fused all section results to achieve the screening of false positive nodules. …”
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Optimal path selection and secured data transmission in underwater acoustic sensor networks: LSTM-based energy prediction. by Sathish Kaveripakam, Ravikumar Chinthaginjala

“…The communication process may be substantially disrupted due to the underwater acoustic channel's time-varying and space-varying features. As a result, the underwater acoustic communication system faces the problems of reducing interference and enhancing communication effectiveness and quality through adaptive modulation. …”
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Use of machine learning for simplification of University Personality Inventory (UPI) by Weihua Guo, Jinsheng Hu, Qi Qiang, Xianke Chen

“…Additionally, we analyzed individual features and feature combinations. Results: Among the three models, the Random Forest model performed the best, with an accuracy of 89.4 %. …”
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An Inclusive review on deep learning techniques and their scope in handwriting recognition by Sukhdeep Singh, Sudhir Rohilla, Anuj Sharma

“… Deep learning expresses a category of machine learning algorithms that have the capability to combine raw inputs into intermediate features layers. These deep learning algorithms have demonstrated great results in different fields. …”
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Association of Hyaluronic Acid-Enriched Transfer Medium (HETM) with Clinical Pregnancy Outcome in Women Undergoing Frozen-Thawed Embryo Transfer (FET) by Achal Warhade, Akash More, Namrata Choudhary, Ganesh Kalaskar, Prajwal Warhade

“…Background: Recurrent implantation failure is one of the most important problems in the assisted reproduction technologies, such as women who want frozen-thawed embryo transfers. …”
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Generative adversarial networks for creating realistic training data for machine learning-based segmentation of FIB tomography data by Trushal Sardhara, Christian J Cyron, Martin Ritter, Roland C Aydin

“…However, these simulations are computationally expensive, and the resulting synthetic imaging data still differs from real FIB tomography data in terms of the statistical distribution of various features. In this study, we propose a novel approach to overcome both problems, i.e. requiring high computation time and difference in data distribution, using generative adversarial networks.…”
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Smartification furniture manufacturing: A furniture prototype with thermal-based sensors (Visions and Challenges) by Lina Nageb Fewella

“…This methodology also provides a development concept for common pre-manufactured furniture and techniques for incorporating interactive features. The study encountered multiple problems in practical implementation, the foremost being the lack of existing industrial design models. …”
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Research on prediction algorithm of effluent quality and development of integrated control system for waste-water treatment by JianWun Lai

“…Suboptimal treatment efficiency and use of resources are the results of the methods used for WWTCS, which are not highly susceptible to changing impact features and complex biological systems. The present study presented a prediction algorithm and an Integrated Control System (ICS) to address the problems of conventional methods. …”
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