Cassava Diseases Classification using EfficientNet Model with Imbalance Data Handling by Stephany Octaviani Ngesthi, Lili Ayu Wulandhari

“…To tackle this imbalance issue, the authors compared several imbalance data handling methods commonly used for image classification, including SMOTE (Synthetic Minority Oversampling Technique), basic augmentation, and neural style transfer, to be applied before fed into EfficientNet. …”
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A Comparative Study of Machine Learning Based Classifications on Lung Cancer Detection by A. Rakesh, Radhamani Ellapparaj

“…Despite advances in machine learning, achieving higher accuracy in classification models for lung cancer remains a persistent challenge. …”
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Arabic Speech Classification Method Based on Padding and Deep Learning Neural Network by Asroni Asroni, Ku Ruhana Ku-Mahamud, Cahya Damarjati, Hasan Basri Slamat

“…Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. …”
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Self-supervised learning reduces label noise in sharp wave ripple classification by Saber Graf, Pierre Meyrand, Cyril Herry, Tiaza Bem, Feng-Sheng Tsai

“…Abstract In the field of electrophysiological signal analysis, the classification of time-series datasets is essential. However, these datasets are often compromised by the prevalent issue of incorrect attribution of labels, known as label noise, which may arise due to insufficient information, inappropriate assumptions, specialists’ mistakes, and subjectivity, among others. …”
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Beyond Information Distortion: Imaging Variable-Length Time Series Data for Classification by Hyeonsu Lee, Dongmin Shin

“…In real-world applications, these data are often collected with variable sample lengths, which can pose challenges for classification models that typically require fixed-length inputs. …”
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Utility of immunohistochemistry on bone marrow trephine biopsy for the diagnosis and classification of acute leukemia by H Sudha Rani, Monalisa Hui, Megha S Uppin, Shantveer G Uppin, G Sadashivudu, Tara Roshni Paul

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Detection and classification of ChatGPT-generated content using deep transformer models by Mahdi Maktabdar Oghaz, Lakshmi Babu Saheer, Kshipra Dhame, Gayathri Singaram

“…Several studies have attempted to distinguish and classify AI-generated textual content from human-authored work, but their performance remains questionable, particularly for AI models utilizing large language models like ChatGPT.MethodsTo address this issue, we compiled a dataset consisting of both human-written and AI-generated (ChatGPT) content. …”
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A Developed LSTM-Ladder-Network-Based Model for Sleep Stage Classification by Ruichen Li, Bei Wang, Tao Zhang, Takenao Sugi

“…The developed model is implemented based on a transductive learning scheme to avoid the issue of accuracy loss caused by individual differences. …”
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Towards transparency in AI: Explainable bird species image classification for ecological research by Samparthi V.S. Kumar, Hari Kishan Kondaveeti

“…This study addresses these issues by employing Explainable Artificial Intelligence (XAI) to enhance the transparency of deep learning models for bird species image classification. …”
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Hyper-LKCNet: Exploring the Utilization of Large Kernel Convolution for Hyperspectral Image Classification by Rong Liu, Zhilin Li, Jiaqi Yang, Jian Sun, Quanwei Liu

“…Large kernel convolution provides the inspiration for the above issue. To explore the potential of large kernel convolution, we propose a hyperspectral image (HSI) classification algorithm in this article that utilizes a large kernel convolution module combined with multiscale coattention and an adaptive geometric feature (AGF) classifier, named Hyper-LKCNet. …”
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EEG-Channel-Temporal-Spectral-Attention Correlation for Motor Imagery EEG Classification by Wei-Yen Hsu, Ya-Wen Cheng

“…However, most current methods do not consider EEG feature information in spatial, temporal and spectral domains, and the structure of these models cannot effectively extract discriminative features, resulting in limited classification performance. To address this issue, we propose a novel text motor-imagery EEG discrimination method, namely wavelet-based temporal-spectral-attention correlation coefficient (WTS-CC), to simultaneously consider the features and their weighting in spatial, EEG-channel, temporal and spectral domains in this study. …”
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Classification with reject option: Distribution-free error guarantees via conformal prediction by Johan Hallberg Szabadváry, Tuwe Löfström, Ulf Johansson, Cecilia Sönströd, Ernst Ahlberg, Lars Carlsson

“…ML with reject option addresses this issue by abstaining from making a prediction if it is likely to be incorrect. …”
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Ensemble Network-Based Distillation for Hyperspectral Image Classification in the Presence of Label Noise by Youqiang Zhang, Ruihui Ding, Hao Shi, Jiaxi Liu, Qiqiong Yu, Guo Cao, Xuesong Li

“…Deep learning has made remarkable strides in hyperspectral image (HSI) classification, significantly improving classification performance. …”
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Strategies to alleviate flickering: Bayesian and smoothing methods for deep learning classification in video by Noah Miller, Glen Ryan Drumm, Lance Champagne, Bruce Cox, Trevor Bihl

“…Bayesian neural networks are a potential remedy to this issue using Bayesian priors. This research compares a traditional video classification neural network to its Bayesian equivalent based on performance and capabilities. …”
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Understanding the Role of Diversity in Ensemble-Based AutoML Methods for Classification Tasks by Salomey Osei, Andres R. Masegosa, Antonio D. Masegosa

“…This study uses novel theoretical frameworks related to the role of diversity in ensembles, which were recently proposed, to shed light on this issue. In this work, we focus on AutoML methods for classification tasks. …”
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Oil and Gas Industry Companies’ Classification and Ordering by the Level of Investment Attractiveness Algorithm by Chernova Natalia L., Serhiienko Olena A., Huz Ostap B.

“…Investment development of industries is an important factor in their overall development, therefore the issue of classification and ordering of companies in the oil and gas industry by the level of investment attractiveness becomes particularly relevant. …”
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Bridging Sensor Gaps via Attention-Gated Tuning for Hyperspectral Image Classification by Xizhe Xue, Haokui Zhang, Haizhao Jing, Lijie Tao, Zongwen Bai, Ying Li

“…Data-driven hyperpectral image (HSI) classification methods require high-quality labeled HSIs, which are often costly to obtain. …”
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Real Time Vehicle Classification Using Deep Learning—Smart Traffic Management by Tejasva Maurya, Saurabh Kumar, Mritunjay Rai, Abhishek Kumar Saxena, Neha Goel, Gunjan Gupta

“…In response to this critical issue, this research presents a novel deep learning‐based approach to vehicle classification aimed at enhancing traffic management systems and road safety. …”
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End-to-End Horse Gait Classification in Uncontrolled Environments Using Inertial Sensors by Mahaut Gerard, Sandrine Hanne-Poujade, Guillaume Dubois, Henry Chateau, Neila Mezghani

“…We divided the six gaits classification task into two subtasks: a four-gaits classification and a gallop-specific classification. …”
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Classification of management tools in small business organizations for developing a sales funnel by E. R. Tolstova, L. V. Silakova

“…The following problems are identified for small businesses: the issue of scaling, the need to automate workflows, collecting feedback and feedback from customers, processing applications, great competition in the market, parallelization of workflows, organization of hierarchy in the workflow. …”
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