Pest classification: Explainable few-shot learning vs. convolutional neural networks vs. transfer learning by Nitiyaa Ragu, Jason Teo

“…A comparative analysis was conducted against Convolutional Neural Network (CNN) and transfer learning models using full pest images, half pest images, and Malaysian pest images. …”
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Improving brain tumor classification: An approach integrating pre-trained CNN models and machine learning algorithms by Mohamed R. Shoaib, Jun Zhao, Heba M. Emara, Ahmed S. Mubarak, Osama A. Omer, Fathi E. Abd El-Samie, Hamada Esmaiel

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Learning spatio-temporal context for basketball action pose estimation with a multi-stream network by Zhihao Zhang, Wenyue Liu, Yuan Zheng, Linkang Du, Lezhong Sun

“…To tackle these issues, this paper proposes a basketball action pose estimation framework, which first leverages a multi-dimensional data stream network to extract spatial, temporal, and contextual information separately. …”
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CSCA-YOLOv8: A lightweight network model for evaluating drought resistance in mung bean. by Dongshan Jiang, Jinyang Liu, Haomiao Zhang, Wenxiang Liang, Ziqiu Luo, Wenlong An, Shicong Li, Xin Chen, Xingxing Yuan, Shangbing Gao

“…Finally, the SIoU loss function is used to replace CIoU to accelerate the convergence of the model. In the actual data analysis, we used the collected 4808 chlorophyll fluorescence images of the natural mung bean population under drought stress to make the Mungbean Drought Datatset(MDD) and made classification labels for each image according to different drought resistance levels, which were 0, 1, 2, 3, 4 and 5. …”
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Leveraging Social Media Data to Understand the Impact of COVID-19 on Residents' Dietary Behaviors: Observational Study by Chuqin Li, Alexis Jordan, Yaorong Ge, Albert Park

“…We used transfer learning and a pretrained ResNet-101 neural network to classify images into 4 health categories: definitely healthy, healthy, unhealthy, and definitely unhealthy. …”
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Automatic Leather Defect Detection and Classification Using Single-Channel and Multi-Channel Neural Networks by Majda Curtic-Hodzic, Aldina Ajkunic, Emir Sokic, Almir Salihbegovic, Lejla Arapovic, Nedim Osmic, Samim Konjicija

“…The suggested methodology enhances the research domain of leather inspection automation by creating an openly accessible image dataset, performing a comparative analysis of detection models and creating software tools for data preparation. …”
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Artificial Intelligence in the Diagnostic Use of Transcranial Doppler and Sonography: A Scoping Review of Current Applications and Future Directions by Giuseppe Miceli, Maria Grazia Basso, Elena Cocciola, Antonino Tuttolomondo

“…Artificial intelligence (AI) is revolutionizing the field of medical imaging, offering unprecedented capabilities in data analysis, image interpretation, and decision support. …”
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Customer Behavior and Brand Promotion in Professional Sports Clubs: Developing Social Networks Marketing Model by Rasool Nazari, Elham Moshkelgosha, Mohsen Loghmani

“…Data collection was done using standard questionnaires, and data analysis was done using structural equation modeling using Smart PLS and SPSS software.Findings: We showed that the antecedents of social network marketing include social business drivers, brand experience, and perceived values ​​from branded web advertisements, which have a positive and significant effect on customer business relationships and brand health through customer brand engagement and brand attitude. …”
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Intelligent Defect Identification Based on PECT Signals and an Optimized Two-Dimensional Deep Convolutional Network by Baoling Liu, Jun He, Xiaocui Yuan, Huiling Hu, Xuan Zeng, Zhifang Zhu, Jie Peng

“…The time-frequency representation (TFR) obtained by the GWT method not only has excellent ability in terms of the transient component analysis but also is less affected by the reduction of image size; the proposed optimized DCNN can accurately identify defect types without manual feature extraction. …”
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MRI-based insights into brain structural and functional alterations in schizophrenia treated with risperidone by Hangyu Li, Xinyue Chen, Shiji Peng, Ying Li, Rui Yu, Kaike Liao, Nian Liu

“…This review offers a summary of current findings on the impact of risperidone treatment on gray matter, white matter, and functional brain activity and connectivity in SZ patients, including its neural mechanisms, therapeutic benefits, and potential side effects.MethodsLiteratures on the use of risperidone for treating schizophrenia were searched in PubMed, Embase and Web of Science analyzing and summarizing the alterations in brain structure and function associated with risperidone.ResultsThrough the analysis and summary, it was found that risperidone treatment in SZ patients can have a marked effect on different structural and functional regions including the prefrontal lobe, temporal lobe, cingulate gyrus, corona radiata, basal ganglia, and corpus callosum.ConclusionMost research has focused on short-term effects, with limited longitudinal data to assess long-term efficacy and side effects, more researches could be added in the future. …”
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An eXplainable deep learning model for multi-modal MRI grading of IDH-mutant astrocytomas by Hamail Ayaz, Oladosu Oladimeji, Ian McLoughlin, David Tormey, Thomas C. Booth, Saritha Unnikrishnan

“…This study proposes a novel non-invasive approach for grading IDH-Mutant-astrocytomas using a Light-weight Attention Network (LAN) that integrates multi-modal MRI data, including both conventional and advanced MRI modalities. …”
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Enhancing Kármán Vortex Street Detection via Auxiliary Networks Incorporating Key Atmospheric Parameters by Yihan Zhang, Zhi Zhang, Qiao Su, Chaoyue Wu, Yuqi Zhang, Daoyi Chen

“…Utilizing reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF-ERA5), representative atmospheric features are extracted and subjected to feature permutation importance (PFI) analysis to quantitatively evaluate the influence of each parameter on the detection task. …”
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A survival prediction network based on multi-scale hypergraph enhancement and cross-modal refinement by Chaofeng Yang, Yongjie Liang, Fan Qin, Yulong Cao, Peiyuan Wang, Jiaying Fan, Bizhong Wei

“…This paper proposes a survival prediction network based on multi-scale hypergraph enhancement and cross-modal refinement (MSHG-CMR), which achieves deep joint modeling and efficient information fusion of pathological images and multi-omics data by integrating multi-scale hypergraph enhancement and cross-modal refinement Transformer technology. …”
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Method for Preprocessing Video Data for Training Deep-Learning Models for Identifying Behavioral Events in Bio-Objects by Marina Barulina, Alexander Andreev, Ilya Kovalenko, Ilya Barmin, Eduard Titov, Danil Kirillov

“…The method is based on combining information about a behavioral event presented in a sequence of frames with the addition of a native image and subsequent boundary detection using the Sobel filter. …”
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Falsifying computational models of endothelial cell network formation through quantitative comparison with in vitro models. by Tessa M Vergroesen, Vincent Vermeulen, Roeland M H Merks

“…We extract a variety of dynamical characteristics of endothelial cell network formation using a custom time-lapse video analysis pipeline in ImageJ. …”
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KHNN: Hypercomplex-valued neural networks computations via Keras using TensorFlow and PyTorch by Agnieszka Niemczynowicz, Radosław A. Kycia

“…This tool provides a streamlined approach for developing models that leverage hypercomplex numbers, enhancing performance in areas like image processing and signal analysis, and fostering innovation in machine learning. …”
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International trade market forecasting and decision-making system: multimodal data fusion under meta-learning by Yiming Bai, Muhammad Asif

“…Traditional market analysis tools primarily rely on unidimensional data, such as historical trading records and price trends. …”
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Multi-task advanced convolutional neural network for robust lymphoblastic leukemia diagnosis, classification, and segmentation by Sercan Yalcin, Zuhal Cetin Yalcin, Muhammed Yildirim, Bilal Alatas

“…This article introduces a novel multi-task advanced convolutional neural network (MTA-CNN) framework for ALL detection in medical imaging data by simultaneously performing, expression classification, and disease detection. …”
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Octascope: A Lightweight Pre-Trained Model for Optical Coherence Tomography by Haoyang Cui, Chen Wang, Paul Calle, Yunlong Liu, Qinghao Zhang, Sinaro Ly, Justin Reynolds, Feng Yan, Ke Zhang, Ronghao Liu, Junyuan Liu, Kar-Ming Fung, Zhongxin Yu, Ajay Jain, Qinggong Tang, Chongle Pan

“…However, OCT image analysis using deep learning is hampered by limited diverse training data to meet performance requirements and high inference latency for real-time applications. …”
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Mitigating bias in prostate cancer diagnosis using synthetic data for improved AI driven Gleason grading by Derek J. Van Booven, Cheng-Bang Chen, Oleksandr N. Kryvenko, Sanoj Punnen, Victor Sandoval, Sheetal Malpani, Ahmed Noman, Farhan Ismael, Yujie Wang, Rehana Qureshi, Joshua M. Hare, Himanshu Arora

“…Machine learning (ML) models offer potential for automated grading but are limited by dataset biases, staining variability, and data scarcity, reducing their generalizability. This study employs generative adversarial networks (GANs) to generate high-quality synthetic histopathological images to address these challenges. …”
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