Adversarial Validation in Image Classification Datasets by Means of Cumulative Spectral Gradient by Diego Renza, Ernesto Moya-Albor, Adrian Chavarro

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Study of spectral overlap and heterogeneity in agriculture based on soft classification techniques by Shubham Rana, Salvatore Gerbino, Petronia Carillo

“…This study explores the application of fuzzy soft classification techniques combined with vegetation indices to address spectral overlap and heterogeneity in agricultural image processing. …”
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Multiple Classifier System for Handling Imbalanced and Overlapping Datasets on Multiclass Classification by Dessy Siahaan, Anwar Fitrianto, Khairil Anwar Notodiputro

“…The performance of classification models suffer when the dataset contains imbalanced and overlapping data. …”
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Geomorphological mapping of the state of Paraná with digital classification method of landform patterns by Claudinei Taborda da Silveira, Ricardo Michael Pinheiro Silveira, Willian Bortolini, Victor Pierobom de Almeida

“…A Digital Terrain Model (MDT) was used to obtain three variables: 1) altimetric amplitude (AA), 2) average slope (AS) and 3) topographic position index (TPI), which were combined for classification compatible with the fourth geomorphological taxon, at a scale of 1:100,000. …”
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Performance Analysis of Resampling Techniques for Overcoming Data Imbalance in Multiclass Classification by Anggit Larasati, Sugiyarto Surono, Aris Thobirin, Deshinta Arrova Dewi

“…By integrating the Convolutional Neural Network model, the performance of the classification process can be analyzed effectively and efficiently. …”
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Baby Cry Classification Using Ensemble Learning and Whisper Method Comparison by I Putu Yogi Prasetya Dharmawan, I Made Agus Dwi Suarjaya, Wayan Oger Vihikan

“…Baby cry classification is an important topic in Machine Learning, especially in the healthcare field, as crying is the primary form of communication for infants to convey their needs or conditions. …”
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A weighted difference loss approach for enhancing multi-label classification by Qiong Hu, Masrah Azrifah Azmi Murad, Azreen Bin Azman, Nurul Amelina Nasharuddin

“…To address this, we introduce a novel Weighted Difference Loss (WDL) framework. WDL operates on three core principles: (1) transforming labels into a normalized distribution to model their relative proportions; (2) computing learnable, weighted differences across this distribution to explicitly capture inter-label dynamics and trends; and (3) employing a label-shuffling augmentation to ensure the model learns intrinsic, order-invariant relationships. …”
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THE TOPONYMY OF THE VILLAGE OF PADESH, BLAGOEVGRAD AREA – SEMANTIC CLASSIFICATION AND STRUCTURAL SPECIFICS by Nadelina Ivova

“…It represents a semantic classification of the place names and observes their structural specifics. …”
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Road Event Detection and Classification Algorithm Using Vibration and Acceleration Data by Abiel Aguilar-González, Alejandro Medina Santiago

“…Our method utilizes vibration and acceleration data in three axes (x, y, z) to classify events in a robust and scalable manner. …”
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Automated Visual Inspection for Precise Defect Detection and Classification in CBN Inserts by Li Zeng, Feng Wan, Baiyun Zhang, Xu Zhu

“…This paper proposes an automated detection and classification system using machine vision to scrutinize these surface defects. …”
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Automated classification of MESSENGER plasma observations via unsupervised transfer learning by Vicki Toy-Edens, Wenli Mo, Robert C. Allen, Sarah K. Vines, Savvas Raptis

“…While our method requires modifications to the model from post-cleaning rules due to instrument effects, it allows for rapid classification using just a few examples to generate post-cleaning rules. …”
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Comprehensive Study on Zero-Shot Text Classification Using Category Mapping by Kai Zhang, Qiuxia Zhang, Chung-Che Wang, Jyh-Shing Roger Jang

“…This paper employs three strategies to improve the accuracy and generalization of pre-trained models in zero-shot text classification tasks: 1) Utilizing a pre-trained model that transforms inputs into a standardized multiple-choice format. 2) Constructing a text classification training set using Wikipedia text data to fine-tune the pre-trained model; 3) Proposing a zero-shot category mapping method based on GloVe text similarity, using Wikipedia categories as substitutes for text labels. …”
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Confidence-Aware Ship Classification Using Contour Features in SAR Images by Al Adil Al Hinai, Raffaella Guida

“…Predictions were then assigned to one of three confidence levels (high, moderate, or low), with the Gaussian-based approach showing superior correlation with classification accuracy compared to other methods.…”
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Adaptive Vision-Based Gait Environment Classification for Soft Ankle Exoskeleton by Gayoung Yang, Jeong Heo, Brian Byunghyun Kang

“…An experimental study evaluated the classification algorithm and soft ankle exosuit performance through three conditions using kinematic analysis and muscle activation measurements. …”
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Neural Network-Based Sentiment Classification of Russian Sentences into Four Classes by Maksim A. Kosterin, Ilya V. Paramonov

“…Mixed sentiment sentences contain positive and negative sentiments simultaneously.To solve the problem, the following tools were applied: the attention-based LSTM neural network, the dual attention-based GRU neural network, the BERT neural network with several modifications of the output layer to provide classification into four classes. The experimental comparison of the efficiency of various neural networks were performed on three corpora of Russian sentences. …”
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Enhancing the classification of seismic events with supervised machine learning and feature importance by Eman L. Habbak, Mohamed S. Abdalzaher, Adel S. Othman, HA Mansour

“…The proposed approach considers a collection of 837 events (EQs and QBs) with local magnitudes of $$1.5 \le M_{L} \le 3.3$$ 1.5 ≤ M L ≤ 3.3 from the Egyptian National Seismic Network (ENSN) seismic event catalog between 2009 and 2015. …”
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Domain generalization for image classification based on simplified self ensemble learning. by Zhenkai Qin, Xinlu Guo, Jun Li, Yue Chen

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Domain-Invariant Few-Shot Contrastive Learning for Hyperspectral Image Classification by Wenchen Chen, Yanmei Zhang, Jianping Chu, Xingbo Wang

“…Experimental results on three widely used HSI datasets demonstrate that our method significantly outperforms existing techniques in few-shot classification tasks.…”
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Enhancing Sentiment and Emotion Classification with LSTM-Based Semi-Supervised Learning by Rochmat Husaini, Nur Heri Cahyana, Wisnalmawati Wisnalmawati, Tri Mardiana, Yuli Fauziah

“…This study employed four Indonesian datasets—Ridife (sentiment classification), Emotion Indonlu (emotion classification), Sentiment Indonlu (sentiment classification), and Hate Speech (offensive content detection). …”
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Comparison of deep learning models in automatic classification of coffee bean species by Adem Korkmaz, Tarık Talan, Selahattin Koşunalp, Teodor Iliev

“…To achieve this, images of three different coffee bean species (Starbucks Pike Place, Espresso, and Kenya) were classified using five CNN-based models: Xception, DenseNet201, InceptionV3, InceptionResNetV2, and DenseNet121. …”
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