Species distribution modelling using MaxEnt: overview and prospects by Yuliia Novoseltseva

“…It is precisely this feature of MaxEnt that makes it an indispensable tool for biodiversity research based on historical data. …”
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DLML-PC: an automated deep learning and metric learning approach for precise soybean pod classification and counting in intact plants by Yixin Guo, Jinchao Pan, Xueying Wang, Hong Deng, Hong Deng, Mingliang Yang, Mingliang Yang, Enliang Liu, Qingshan Chen, Qingshan Chen, Rongsheng Zhu, Rongsheng Zhu

“…However, these methods mainly focus on the total number of pods, ignoring the differences between different pod types and do not consider the time-consuming and labor-intensive problem of picking pods from the whole plant. In this study, a deep learning approach was used to directly detect the number of different types of pods on non-disassembled plants at the maturity stage of soybean. …”
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Determined the Edges Using the ant Colony Algorithm and Apply them to Medical Images by Maha Rahman Hasso, Aseel Ali

“…Every ant build solutions to the problem, and uses the information grouped about the features and performance of the private problem, to change the look to the ant problem. …”
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Human action recognition method based on multi-view semi-supervised ensemble learning by Shengnan CHEN, Xinmin FAN

“…Mass labeled data are hard to get in mobile devices.Inadequate training leads to bad performance of classifiers in human action recognition.To tackle this problem, a multi-view semi-supervised ensemble learning method was proposed.First, data of two different inertial sensors was used to construct two feature views.Two feature views and two base classifiers were combined to construct co-training framework.Then, the confidence degree was redefined in multi-class task and was combined with active learning method to control predict pseudo-label result in each iteration.Finally, extended training data was used as input to train LightGBM.Experiments show that the method has good performance in precision rate, recall rate and F1 value, which can effectively detect different human action.…”
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Real time counting method for coal mine drill pipes based on deep learning by Fukai ZHANG, Yiran SUN, Xufeng WU, Aijun LI, Peiyang LI, Dengke WANG, Guan YUAN, Shan ZHAO, Haiyan ZHANG

“…Experiments on the CMDPC dataset show that the improved Drill-YOLOv8 model performs well in mAP@0.5 The mAP @ [0.5:0.95] index has increased by 3.0% and 2.7% respectively, effectively solving the problem of false detection and missed detection of drilling head and drill pipe targets under strong light, water vapor, and occlusion environments, and the detection speed has reached 86 frames per second; At the same time, the weighted average error rate of the counting inference algorithm Pipe Count is 2%, showing good robustness against multi scene data, and the processing speed reaches 40 frames per second, meeting real-time counting requirements.…”
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ENDNet: Extra-Node Decision Network for Subgraph Matching by Masaki Shirotani, Motoki Amagasaki, Masato Kiyama

“…Specifically, GNNs generate new node features by aggregating information from adjacent nodes, meaning that even if nodes in the query and data graphs start with identical features, the presence of extraneous nodes or edges in the data graph can distort feature representations and hinder accurate matching. …”
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Neural-Network-Based Synchronization Acquisition with Hankelization Preprocessing by Gyung-Eun Kim, Jung-Hwan Kim, Jong-Ho Lee, Woong-Hee Lee

“…In such environments, the usage of a long synchronization signal is beneficial for ensuring sufficient correlation information and enhancing detection robustness. To address these problems, this paper proposes a novel framework that combines Hankelization-based preprocessing with the operation of a neural network (NN). …”
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Redefining dental image processing: De-convolutional component with residual prolonged bypass for enhanced teeth segmentation by Prasun Kumar, Verma Anil, Mishra Rajiv

“…Therefore, different traditional techniques are employed for the detection of dental problems. However, these classical techniques such as X-Ray and CT scans are considered to be time-consuming, ineffective, and prone to errors due to human intervention. …”
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Recognition Method of Corn and Rice Crop Growth State Based on Computer Image Processing Technology by Li Tian, Chun Wang, Hailiang Li, Haitian Sun

“…The traditional image capturing and processing models have problems of large image segmentation error, excessive feature extraction time, and poor recognition output. …”
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Breast calcifications. Literature review by O. S. Khodorovich, V. A. Solodkiy, V. O. Kleshneva, T. V. Sherstneva, K. V. Ishchenko

“…The problem was considered from the mechanism of formation and morphological features of calcifications in the breast tissue to their radiographic assessment on mammographic images. …”
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Noise Robust Underwater Fishing Net Recognition Based on Range Gated Imaging by Zhensong Xu, Xinwei Wang, Liang Sun, Bo Song, Yue Zhang, Pingshun Lei, Jianan Chen, Jun He, Yan Zhou, Yuliang Liu

“…The proposed SFNR-Net introduces an auxiliary semantic segmentation module (ASSM) to introduce extra semantic information and enhance feature representation under noisy conditions. Besides, to address the problem of unbalanced training data, we employ semantic regulated cycle-consistent generative adversarial network (CycleGAN) as a data augmentation approach. …”
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Dynamic Path Flow Estimation Using Automatic Vehicle Identification and Probe Vehicle Trajectory Data: A 3D Convolutional Neural Network Model by Can Chen, Yumin Cao, Keshuang Tang, Keping Li

“…Therefore, in this paper, the dynamic path flow estimation is based on these two data sources and transformed into a feature learning problem. To fuse the two data sources belonging to different detection ways at the data level, the virtual AVI points, analogous to the real AVI points (turning movements at nodes with AVI detectors), are defined and selected to statically observe the dynamic movement of the probe vehicles. …”
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Label credibility correction based on cell morphological differences for cervical cells classification by Wenbo Pang, Yue Qiu, Shu Jin, Huiyan Jiang, Yi Ma

“…Firstly, a contrastive learning network is used to extract discriminative features from cell images to obtain more similar intra-class sample features. …”
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Research into the Application of ResNet in Soil: A Review by Wenjie Wu, Lijuan Huo, Gaiqiang Yang, Xin Liu, Hongxia Li

“…ResNet outperforms traditional methods by effectively mitigating the vanishing gradient problem, enabling deeper network training, enhancing feature extraction, and improving accuracy in complex pattern recognition tasks. …”
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Deep Unified Model For Face Recognition Based on Convolution Neural Network and Edge Computing by Muhammad Zeeshan Khan, Saad Harous, Saleet Ul Hassan, Muhammad Usman Ghani Khan, Razi Iqbal, Shahid Mumtaz

“…Usually, for face recognition, scale-invariant feature transforms (SIFT) and speeded up robust features (SURF) have been used by the research community. …”
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A lightweight semantic segmentation method for concrete bridge surface diseases based on improved DeeplabV3+ by Zhiyuan Yu, Chunquan Dai, Xiaoming Zeng, Yunlong Lv, Haisheng Li

“…Abstract Due to the similar features of different diseases and insufficient semantic information of small area diseases in the surface disease image of concrete bridges, the existing semantic segmentation models for identifying surface diseases in concrete bridges suffer from problems such as large number of parameters, insufficient feature extraction, and low segmentation accuracy. …”
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Machine Learning-Based Damage Diagnosis in Floating Wind Turbines Using Vibration Signals: A Lab-Scale Study Under Different Wind Speeds and Directions by John S. Korolis, Dimitrios M. Bourdalos, John S. Sakellariou

“…This study investigates, for the first time, the complete (all stages) damage diagnosis problem by employing well-established ML SHM methods and conducting hundreds of experiments on a lab-scale FWT model operating under different wind speeds and directions, both in healthy and damaged states. …”
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Extraction Method of Coronary Artery Blood Vessel Centerline in CT Coronary Angiography by Xiaodong Sheng, Tao Fan, Xiaoqi Jin, Jing Jin, Zhixian Chen, Guanqun Zheng, Min Lu, Zongcheng Zhu

“…Finally, the pseudo vascular centerline is removed using the vascular topology feature detection method. The experimental results show that the method can accurately extract the blood vessel center line, direction vector and other information in the coronary angiography image without manual intervention, and can be used in the computer-assisted diagnosis and treatment process of clinical cardiovascular disease.…”
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BFER-Net: Babies Facial Expression Recognition Model Using ResNet12 Enabled Few-Shot Embedding Adaptation and Convolutional Block Attention Modules by Sumiya Arafin, Adnan Ferdous Ashrafi, Md. Golam Rabiul Alam, Ashis Talukder

“…Here, we have deployed the feature extraction process. A Convolutional Block Attention Module (CBAM) was integrated into the Modified ResNet12 architecture. …”
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Anytime Optimal Trajectory Repairing for Autonomous Vehicles by Kailin Tong, Martin Steinberger, Martin Horn, Selim Solmaz, Daniel Watzenig

“…Our paper introduces a groundbreaking approach by formulating an optimal trajectory repairing problem and proposing an innovative and efficient framework for critical timing detection and trajectory repairing. …”
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