Lithuania’s Binary Worker Classification Vs. A Teleological Interpretation of the EU’s ‘Worker’ Concept by Germany and the UK by Lauschke Hans

“…The article explores whether Lithuania’s concept of darbuotojas (employee) and its rigid binary classification of work relationships is challenged by an evolving European employment law landscape, shaped by a rise of unconventional work relationships that blur the lines between employees and self-employed persons. …”
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Enhanced Fault Detection in Photovoltaic Panels Using CNN-Based Classification with PyQt5 Implementation by Younes Ledmaoui, Adila El Maghraoui, Mohamed El Aroussi, Rachid Saadane

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Fabric Faults Robust Classification Based on Logarithmic Residual Shrinkage Network in a Four-Point System by Canan Tastimur, Erhan Akin, Mehmet Agrikli

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Classification of Arabic Alphabets Using a Combination of a Convolutional Neural Network and the Morphological Gradient Method by Mouhssine EL ATILLAH, Khalid EL FAZAZY, Jamal Riffi

“… The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. …”
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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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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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A stochastic optimization method for economic microgrid operation based on "source-load operation" mode classification by ZHOU Hang, MA Lihong, LI Zhongzhong, WANG Haisheng, LI Sifan, ZHANG Changjun, FU Linbei

“…The volatility of renewable energy output and the randomness of user-side electricity consumption behavior have led to increasing source-load uncertainties， posing significant operational risks to microgrids. To address this issue， an economic operation decision-making method for microgrids based on source-load operation mode classification is proposed to achieve economic operation under uncertain conditions. …”
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A Novel Neural Network Framework for Automatic Modulation Classification via Hankelization-Based Signal Transformation by Jung-Hwan Kim, Jong-Ho Lee, Oh-Soon Shin, Woong-Hee Lee

“…Automatic modulation classification (AMC) is a fundamental technique in wireless communication systems, as it enables the identification of modulation schemes at the receiver without prior knowledge, thereby promoting efficient spectrum utilization. …”
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TGF-Net: Transformer and gist CNN fusion network for multi-modal remote sensing image classification. by Huiqing Wang, Huajun Wang, Linfen Wu

“…Although deep learning technology has achieved certain results in remote sensing image classification, it still has certain challenges for multi-modality remote sensing data classification. …”
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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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Semantic consistency enhancement and contribution-driven network for partial multi-view incomplete multi-label classification by Yishan Jiang, Lian Zhao, Zhixian Jiang, Yinghao Ye, Xiaohuan Lu

“…Currently, some frameworks have been introduced to address the complex issue of partial multi-view incomplete multi-label classification, but they frequently overlook the impact of view quality on the learning of semantic information. …”
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A novel three-way distance-based fuzzy large margin distribution machine for imbalance classification by Li Liu, Jinrui Guo, Ziqi Yin, Rui Chen, Guojun Huang

“…Abstract Class imbalance is a prevalent issue in practical applications, which poses significant challenges for classifiers. …”
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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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EmoFusion: An integrated machine learning model leveraging embeddings and lexicons to improve textual emotion classification by Anjali Bhardwaj, Muhammad Abulaish

“…This paper presents EmoFusion, an integrated machine learning model that improves emotion classification in textual data by integrating pre-trained word embeddings and emotion lexicons. …”
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TI-RADS CLASSIFICATION SYSTEM AND ITS FIRST APPLICATION IN THE ULTRASOUND DIAGNOSIS DEPARTMENT IN THE MULTI-SPECIALITY HOSPITAL by A. A. Kvasova, A. N. Katrich

“…The most common classification system is TI-RADS.Objective. To evaluate the TI-RADS classification efficacy for the thyroid gland nodular tumor diagnosis in a multispecialty hospital.Materials and Methods. …”
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A Multi-Source Data-Driven Analysis of Building Functional Classification and Its Relationship with Population Distribution by Dongfeng Ren, Xin Qiu, Zehua An

“…Existing research mainly focuses on the relationship between land functions and population distribution at the macro scale, while neglecting the finer-grained, micro-scale impact of building functionality on population distribution. To address this issue, this study integrates multi-source geospatial and spatio-temporal big data and employs the XGBoost algorithm to classify buildings into five functional categories: residential, commercial, industrial, public service, and landscape. …”
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Designing a hybrid stack ensemble model to enhance sepsis classification using data triangulation approach by Safiya Parvin A․, Saleena B․

“…Sepsis is a major health issue affecting newborns, often caused by factors such as premature birth, birth asphyxia, pneumonia, and meningitis. …”
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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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Classification of the Tasks of Local Governmental Units in Poland in the Light of Fundamental Legal Acts — Discussion of Selected Aspects by Marta Mulawa

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Data Augmentation For Sorani Kurdish News Headline Classification Using Back-Translation And Deep Learning Model by Soran Badawi

“…With the increase in the volume of news articles and headlines being generated, it is becoming more difficult for individuals to keep up with the latest developments and find relevant news articles in the Kurdish language. To address this issue, this paper proposes a novel data augmentation approach for improving the performance of Kurdish news headline classification using back-translation and a proposed deep learning Bidirectional Long Short-Term Memory (BiLSTM) model. …”
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