Detection and classification of hypertensive retinopathy based on retinal image analysis using a deep learning approach by Bambang Krismono Triwijoyo, Ahmat Adil, Muhammad Zulfikri

“…Background: The issue is that most heart attacks and strokes happen unexpectedly to people who have signs of high blood pressure that are not identified in time for treatment. …”
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MSALNet: a multi-scale adaptive learning network for high-resolution remote sensing scene classification by Chao Yang, Chengbo Wei, Yiming Zhao, Liming Wang, Peigang Xu, Kunlun Qi, Yuanzheng Shao, Huayi Wu

“…High-resolution remote sensing (HRS) images often feature objects of varying sizes within the same scene, presenting significant challenges for conventional CNN with fixed-size receptive fields. To address this issue, we propose a multi-scale adaptive learning network (MSALNet) that learns optimal scales in a weakly supervised manner and efficiently fuses multiscale features to enhance feature integration and representation across varying object scales. …”
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Transformer-based multiple instance learning network with 2D positional encoding for histopathology image classification by Bin Yang, Lei Ding, Jianqiang Li, Yong Li, Guangzhi Qu, Jingyi Wang, Qiang Wang, Bo Liu

“…Existing methods incorporating positional information often overlook nuanced spatial correlations or use positional encoding strategies that do not fully capture the unique spatial dynamics of pathology images. To address this issue, we propose a new framework named TMIL (Transformer-based Multiple Instance Learning Network with 2D positional encoding), which leverages multiple instance learning for weakly supervised classification of histopathological images. …”
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Deep learning-based image classification of sea turtles using object detection and instance segmentation models. by Jong-Won Baek, Jung-Il Kim, Chang-Bae Kim

“…Recently, instance segmentation models have been developed to address this issue by providing more accurate classification of complex images compared to traditional object detection models. …”
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BreastCNet: Breast Cancer Detection, Classification, and Localization Convolutional Neural Network With Advanced Optimization Techniques by Hassan Mahichi, Vahid Ghods, Mohammad Karim Sohrabi, Arash Sabbaghi

“…Breast cancer remains a significant global health issue, primarily affecting females and requiring advanced detection methods to improve patient outcomes. …”
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FLC-Net: Innovative fraud classification in loan applications with dual channel graph advanced neural network by P. Pedda Sadhu Naik, Kalleda Appanolla Architha, Maddela Mahesh, Chitkula Anand, Gaddam Shriya Reddy, Patlola Suraj Reddy

“…Fraudulent loan classification is critical in the financial sector, with global loan fraud losses exceeding $1 billion annually. …”
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Tree Species Classification at the Pixel Level Using Deep Learning and Multispectral Time Series in an Imbalanced Context by Florian Mouret, David Morin, Milena Planells, Cécile Vincent-Barbaroux

“…This paper investigates tree species classification using the Sentinel-2 multispectral satellite image time series (SITS). …”
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ADCGNet: Attention-based dual channel Gabor network towards efficient detection and classification of electrocardiogram images by Joseph Roger Arhin, Xiaoling Zhang, Kenneth Coker, Isaac Osei Agyemang, Wisdom Kwame Attipoe, Francis Sam, Isaac Adjei-Mensah, Emmanuel Agyei

“…Heart disease is a major health issue, and accurate diagnosis of irregular heartbeats and heart failure is crucial. …”
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Less Is More: Brain Functional Connectivity Empowered Generalizable Intention Classification With Task-Relevant Channel Selection by Haowei Lou, Zesheng Ye, Lina Yao, Yu Zhang

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Fine-Grained Feature Extraction in Key Sentence Selection for Explainable Sentiment Classification Using BERT and CNN by Thennakoon Mudiyanselage Anupama Udayangani Gunathilaka, Jinglan Zhang, Yuefeng Li

“…Additionally, sequential models place more emphasis on the latter part of the text, assuming that the emotional aspects are concentrated at the end of the review. To address this issue, we introduce a novel Bidirectional Encoder Representations from Transformers (BERT) based dilated sentence attention deep learning model (Bert_DSENT_Att) for important fine-grained local feature extraction by capturing long-range dependencies within sentences, thereby enabling the selection of key sentences that directly impact multi-class sentiment classification. …”
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SkinEHDLF a hybrid deep learning approach for accurate skin cancer classification in complex systems by Umesh Kumar Lilhore, Yogesh Kumar Sharma, Sarita Simaiya, Roobaea Alroobaea, Abdullah M. Baqasah, Majed Alsafyani, Afnan Alhazmi

“…Abstract Skin cancer represents a significant global public health issue, and prompt and precise detection is essential for effective treatment. …”
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Obfuscated Malware Detection and Classification in Network Traffic Leveraging Hybrid Large Language Models and Synthetic Data by Mehwish Naseer, Farhan Ullah, Samia Ijaz, Hamad Naeem, Amjad Alsirhani, Ghadah Naif Alwakid, Abdullah Alomari

“…Android malware detection remains a critical issue for mobile security. Cybercriminals target Android since it is the most popular smartphone operating system (OS). …”
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Advancing Cloud Classification Over the Tibetan Plateau: A New Algorithm Reveals Seasonal and Diurnal Variations by Fangling Bao, Husi Letu, Huazhe Shang, Xu Ri, Deliang Chen, Tandong Yao, Lesi Wei, Chenqian Tang, Shuai Yin, Dabin Ji, Yonghui Lei, Chong Shi, Yiran Peng, Jiancheng Shi

“…Abstract The cloud classification algorithm widely used in the International Satellite Cloud Climatology Project (ISCCP) tends to underestimate low clouds over the Tibetan Plateau (TP), often mistaking water clouds for high‐level clouds. …”
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The hybrid feature extraction method for classification of adolescence idiopathic scoliosis using Evolving Spiking Neural Network by Nurbaity Sabri, Haza Nuzly Abdull Hamed, Zaidah Ibrahim, Kamalnizat Ibrahim, Mohd Adham Isa, Norizan Mat Diah

“…Machine Learning (ML) models are introduced to overcome this issue and reduce human error. Thus, an appropriate Features Extraction (FE) method is crucial to producing a good ML classification model. …”
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The classification of historical sources on Jesuit practices in the East Slavic region in the late XVI - early XVII centuries by Angela Papazova

“…According to the origin, the sources can be divided into the documents issued by the Society; documents on the Jesuit practices issued by other confessions; documents issued by certain states and their authorities; documents and papers issued by particular individuals. …”
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A Frequency-Shifting Variational Mode Decomposition-Based Approach to MI-EEG Signal Classification for BCIs by Haiqin Xu, Shahzada Ali Hassan, Waseem Haider, Youchao Sun, Xiaojun Yu

“…However, traditional signal decomposition (SD) techniques are hindered by two critical issues, mode mixing and mode aliasing, that compromise the quality of the decomposed signal. …”
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Enhancing heart disease classification with M2MASC and CNN-BiLSTM integration for improved accuracy by Vivek Pandey, Umesh Kumar Lilhore, Ranjan Walia, Roobaea Alroobaea, Majed Alsafyani, Abdullah M. Baqasah, Sultan Algarni

“…To overcome these issues, the research proposed a model for heart disease detection and classification by integrating blockchain technology with a Modified mixed attention-enabled search optimizer-based CNN-Bidirectional Long Short-Term Memory (M2MASC enabled CNN-BiLSTM) model. …”
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The Application of Titulus Finalis, Subscriptions, Total Stichometry in the Textual Classification of Early Printed Cyrillic Liturgical Tetraevangelia by Jerzy Ostapczuk

“…The present study attempts to apply this new typological classification of subscriptions, based on their content, wording and gradual development, in a classification of Early Printed Cyrillic litur­gical Tetraevangelia. …”
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Movement Direction Classification Using Low-Resolution ToF Sensor and LSTM-Based Neural Network by Sejik Oh, Kyoung Min Lee, Seok Young Lee, Nam Kyu Kwon

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Utilizing Feature Selection Techniques for AI-Driven Tumor Subtype Classification: Enhancing Precision in Cancer Diagnostics by Jihan Wang, Zhengxiang Zhang, Yangyang Wang

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