A Comparative Study of Transfer Learning and Fine-Tuning Method on Deep Learning Models for Wayang Dataset Classification by Ahmad Mustafid, Muhammad Murah Pamuji, Siti Helmiyah

“…In this paper, We tried proposing some steps and techniques on how to classify the characters and handle the issue on a small wayang dataset by using model selection, transfer learning, and fine-tuning to obtain efficient and precise accuracy on our classification problem. …”
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A Robust Multivariate Time Series Classification Approach Based on Topological Data Analysis for Channel Fault Tolerance by Seong-Yeon Jeung, Jang-Woo Kwon

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A Network Traffic Anomaly Classification Model Based on Self-Attention Mechanism and Convolutional Gated Recurrent Unit by Yulian Li, Yang Su

“…In the context of accelerated digital transformation, cybersecurity has become a global strategic issue. With the rapid growth of network traffic and the evolving complexity of attack patterns, the stability of information systems and data security face significant challenges. …”
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Classification of Real and Fake Images Using Error Level Analysis Technique and MobileNetV2 Architecture by Muhamad Nur Baihaqi, Aris Sugiharto, Henri Tantyoko

“…Advancements in technology have made image forgery increasingly difficult to detect, raising the risk of misinformation on social media. To address this issue, Error Level Analysis (ELA) feature extraction can be utilized to detect error level variations in lossy-formatted images such as JPEG. …”
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Differentiated Embedded Pilot Assisted Automatic Modulation Classification for OTFS System: A Multi-Domain Fusion Approach by Zhenkai Liu, Bibo Zhang, Hao Luo, Hao He

“…As a prerequisite to demodulation and signal processing, automatic modulation classification (AMC) is essential for OTFS systems. However, a very limited number of works have focused on this issue. …”
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Predicting and Preventing Crime: A Crime Prediction Model Using San Francisco Crime Data by Classification Techniques by Muzammil Khan, Azmat Ali, Yasser Alharbi

“…The crime is difficult to predict; it is random and possibly can occur anywhere at any time, which is a challenging issue for any society. The study proposes a crime prediction model by analyzing and comparing three known prediction classification algorithms: Naive Bayes, Random Forest, and Gradient Boosting Decision Tree. …”
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Improved swin transformer-based thorax disease classification with optimal feature selection using chest X-ray. by Nadim Rana, Yahaya Coulibaly, Ayman Noor, Talal H Noor, Md Imran Alam, Zeba Khan, Ali Tahir, Mohammad Zubair Khan

“…Thus, in this research, a model for thorax disease classification using Chest X-rays is proposed by considering deep learning model. …”
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Real-time bearing fault classification of induction motor using enhanced inception ResNet-V2 by Karan Kumar K, Srihari Mandava

“…However, it is challenging to use Deep Learning techniques to identify bearing defects when the machine is not under load. To resolve this issue, this paper presents the Constant-Q Non-stationary Gabor Transform with enhanced Inception ResNet-V2, proposed for the early-stage classification of ball bearing faults in induction motors. …”
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Utilizing Machine Learning-based Classification Models for Tracking Air Pollution Sources: A Case Study in Korea by Yelim Choi, Bogyeong Kang, Daekeun Kim

“…This study aims to comprehensively evaluate machine learning-based emission source classification models to provide insights into air pollution source tracking and management. …”
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Malignant lymphoma in Eastern India: A retrospective analysis of 455 cases according to World Health Organization classification by Santosh Kumar Mondal, Palash Kumar Mandal, Tarun Kumar Samanta, Subrata Chakaborty, Saptarshi Dutta Roy, Shravasti Roy

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Addressing long-tailed distribution in judicial text for criminal motive classification: a balanced contrastive learning approach by Ting Li, Lewen Mi, Xiangyu Meng, Yongju Jia, Lin Zhao, Qi Zhao, Zihao Wei, Guandong Gao, Xiangxian Li

“…Specifically, CA-BCL first balances the sampling process to alleviate the class imbalance during prototype construction and then applies balanced contrastive learning to improve the model’s ability to generalize to long-tailed categories, leading to better overall classification performance. Our experimental results demonstrate that CA-BCL significantly outperforms existing text classification models in crime motive classification, while also showing strong generalization capabilities on standard text classification benchmark.…”
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DynGraph-BERT: Combining BERT and GNN Using Dynamic Graphs for Inductive Semi-Supervised Text Classification by Eliton Luiz Scardin Perin, Mariana Caravanti de Souza, Jonathan de Andrade Silva, Edson Takashi Matsubara

“…The combination of Bidirecional Encoder Representations from Transformers (BERT) and Graph Neural Networks (GNNs) has been extensively explored in the text classification literature, usually employing BERT as a feature extractor combined with heterogeneous static graphs. …”
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Bathymetry-guided multi-source remote sensing image domain adaptive coral reef benthic habitat classification by Hui Chen, Liang Cheng, Ka Zhang

“…Due to the complexity of marine environments, multi-source remote sensing images often exhibit significant domain shifts caused by differences in imaging conditions and platform orientations, posing challenges to the generalization of substrate classification models. To address this issue, we propose a computationally efficient Bathymetry-Guided Domain Adaptation (BGDA) method. …”
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Advances in ECG and PCG-based cardiovascular disease classification: a review of deep learning and machine learning methods by Asmaa Ameen, Ibrahim Eldesouky Fattoh, Tarek Abd El-Hafeez, Kareem Ahmed

“…This work compares and reports the classification, machine learning, and deep learning algorithms that predict cardiovascular illnesses. …”
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The Place of Vocational Pedagogy in Pedagogical Science System by N. V. Ronzhina

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Comparison of the performance of three classification criteria for Behçet's Disease in a single centre cohort from South India by Vishnu S Chandran, Suma Balan

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Land use and land cover classification and terrestrial ecosystem carbon storage changes in Vietnam based on Sentinel images by Yang Liu, Kun Yang, Zongqi Peng, Tianle Zou, Danni Su, Run Sun, Jingcong Ma

“…This study developed a new land cover classification method based on the phenological characteristics of rice, using the Google Earth Engine (GEE). …”
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Local Auxiliary Spatial–Spectral Decoupling Transformer Network for Cross-Scene Hyperspectral Image Classification by Qiusheng Chen, Zhuoqun Fang, Zhaokui Li, Qian Du, Shizhuo Deng, Tong Jia, Dongyue Chen

“…To overcome this issue, we propose a local auxiliary spatial–spectral decoupling transformer network to ease the learning of global domain-invariant information. …”
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An Exploration of Students’ Misconceptions about the Concept ‘Classification of Animals’ at Secondary Level and Effectiveness of Inquiry Method for Conceptual Change by Anjum NAZ, Abida NASREEN

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SwinConvNeXt: a fused deep learning architecture for Real-time garbage image classification by B. Madhavi, Mohan Mahanty, Chia-Chen Lin, B. Omkar Lakshmi Jagan, Hari Mohan Rai, Saurabh Agarwal, Neha Agarwal

“…The conventional method of segregating waste is a time-consuming and ineffective method that wastes human power and money. To address this issue in real time, sophisticated and sustainable waste management systems need to be implemented. …”
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