Machine Learning and Deep Learning for Crop Disease Diagnosis: Performance Analysis and Review by Habiba Njeri Ngugi, Andronicus A. Akinyelu, Absalom E. Ezugwu

“…Crop diseases pose a significant threat to global food security, with both economic and environmental consequences. Early and accurate detection is essential for timely intervention and sustainable farming. …”
Get full text

Metaparameter optimized hybrid deep learning model for next generation cybersecurity in software defined networking environment by C. Labesh Kumar, Suresh Betam, Denis Pustokhin, E. Laxmi Lydia, Kanchan Bala, Rajanikanth Aluvalu, Bhawani Sankar Panigrahi

“…To ensure optimal performance of the CNN-BiGRU-AM model, hyperparameter tuning is performed by utilizing the seagull optimization algorithm (SOA) model to enhance the efficiency and robustness of the detection system. …”
Get full text

Brown adipose tissue machine learning nnU-Net V2 network using TriDFusion (3DF) by Daniel Lafontaine, Stephanie Chahwan, Gustavo Barraza, Burcin Agridag Ucpinar, Gunjan Kayal, Nicolás Gómez-Banoy, Paul Cohen, John L. Humm, Heiko Schöder

“…The introduction of machine learning algorithms, such as the PET/CT algorithm implemented in the TriDFusion (3DF) Image Viewer, represents a significant advancement in BAT detection. …”
Get full text

Stunting Prediction Modeling in Toddlers Using a Machine Learning Approach and Model Implementation for Mobile Application by Eko Abdul Goffar, Rosa Eliviani, Lili Ayu Wulandhari

“…The literature review section discusses the factors that influence stunting, and these factors are used as features to build a stunting prediction model. Then the features were used to build a model with three machine learning algorithms Extreme Gradient Boosting (XGBoost), Random Forest, and K-Nearest Neighbor (KNN) to build and evaluate models that predict stunting. …”
Get full text

Pengaruh Word Affect Intensities Terhadap Deteksi Ulasan Palsu by Raga Saputra Heri Istanto, Fitra Abdurrachman Bachtiar, Achmad Ridok

“…These features are then combined with features in previous studies and evaluated using several classification algorithms. …”
Get full text

A Generalized Method for Sentiment Analysis across Different Sources by Abubakar M. Ashir

“…To deal with sources devoid of syntactic and grammatical structure, the approach incorporates a ruled-based technique for emoticon detection, word contraction expansion, noise removal, and lexicon-based text preprocessing using lexical features such as part of speech (POS), stop words, and lemmatization for local context analysis. …”
Get full text

Smart Real-time Attendance System for Nigerian Universities by Mikailu Habila, Faseki N. Francisca, Luwani Ishaya, Muhammed Kabir Ahmed, Umar A. Muhammad, Haruna P. Charles

“…The system employs Convolutional Neural Networks (CNNs) and the ArcFace algorithm for facial feature extraction and identity verification. …”
Get full text

A hybrid theoretical–numerical–experimental framework for robust health monitoring of thin-walled hollow composite members using guided waves by Akshay Prakash Kalgutkar, Shirsendu Sikdar, Sauvik Banerjee, Karl Walton, Rakesh Mishra

“…This study introduces a hybrid -numerical–experimental framework for robust detection and characterisation of barely visible damage in HCM using guided waves (GW). …”
Get full text

Comprehensive Fault Diagnosis of Three-Phase Induction Motors Using Synchronized Multi-Sensor Data Collection by Kevin Thomas, Ahasanur Rahman, Wesam Rohouma, Md. Faysal Ahamed, Fariya Bintay Shafi, Md. Nahiduzzaman, Amith Khandakar

“…The dataset, organized into ten distinct CSV files covering various operational states, provides a rich resource for developing and testing fault detection algorithms. A Random Forest classifier trained on this dataset achieved an accuracy of 99.82%, demonstrating its suitability for real-time fault diagnosis and predictive maintenance applications. …”
Get full text

Accurate identification of locally aneuploid cells by incorporating cytogenetic information in single cell data analysis by Ziyi Li, Ruoxing Li, Irene Ganan-Gomez, Hussein A. Abbas, Guillermo Garcia-Manero, Wei Sun

“…PartCNV uses an expectation-maximization (EM) algorithm with mixtures of Poisson distributions and incorporates cytogenetic information to guide the classification. …”
Get full text

A Novel THz Differential Spectral Clustering Recognition Method Based on t-SNE by Tie-Jun Li, Chih-Cheng Chen, Jian-jun Liu, Gui-fang Shao, Christopher Chun Ki Chan

“…Second, we improve computation efficiency by mapping spectrum data samples from high-dimensional space to low-dimensional space by the use of a manifold learning algorithm (t-SNE). Finally, to achieve a visible observation of sample features in low-dimensional space, we use a conditional probability distribution to measure the distance invariant similarity. …”
Get full text

Predicting diabetic peripheral neuropathy through advanced plantar pressure analysis: a machine learning approach by Mehewish Musheer Sheikh, Mamatha Balachandra, Narendra V. G., Arun G. Maiya

“…Explainable AI techniques (SHAP, Eli5, Anchor Explanations) provided insights into feature importance, enhancing model interpretability. …”
Get full text

HASSDE-NAS: Heuristic–Adaptive Spectral–Spatial Neural Architecture Search with Dynamic Cell Evolution for Hyperspectral Water Body Identification by Feng Chen, Baishun Su, Zongpu Jia

“…The accurate identification of water bodies in hyperspectral images (HSIs) remains challenging due to hierarchical representation imbalances in deep learning models, where shallow layers overly focus on spectral features, boundary ambiguities caused by the relatively low spatial resolution of satellite imagery, and limited detection capability for small-scale aquatic features such as narrow rivers. …”
Get full text

Location Research and Picking Experiment of an Apple-Picking Robot Based on Improved Mask R-CNN and Binocular Vision by Tianzhong Fang, Wei Chen, Lu Han

“…Four pairs of feature points from corresponding apples in binocular images are selected to calculate disparity and depth. …”
Get full text

SHARPNESS IMPROVEMENT OF MAGNETIC RESONANCE IMAGES USING A GUIDED-SUBSUMED UNSHARP MASK FILTER by Manar AL-ABAJI, Zohair AL-AMEEN

“…Sometimes, MRI images are obtained blurry due to various inevitable constraints related to the imaging equipment, which affects the detection of important features in the image. Several sharpening methods were introduced, but not all were successful in this task, as artifacts may be introduced, contrast may be changed, and high complexity may be involved. …”
Get full text

Enhancing semi‐supervised contrastive learning through saliency map for diabetic retinopathy grading by Jiacheng Zhang, Rong Jin, Wenqiang Liu

“…Moreover, the performance of these algorithms is hampered by the scarcity of large‐scale, high‐quality annotated data. …”
Get full text

Gamified mHealth System for Evaluating Upper Limb Motor Performance in Children: Cross-Sectional Feasibility Study by Md Raihan Mia, Sheikh Iqbal Ahamed, Samuel Nemanich

“…We applied change point detection (ie, the pruned exact linear time method), signal processing techniques, and other algorithms to calculate movement speed and accuracy from spatiotemporal parameters. …”
Get full text

Identification of Fake Comments in E-Commerce Based on Triplet Convolutional Twin Network and CatBoost Model by Juanjuan Peng

“…Compared with the other two comparison algorithms, the detection time required by the proposed model was the shortest at 115us and consumed the least amount of resources. …”
Get full text

Plantention: A general-purpose, lightweight and attention-based model for multi-crop leaf disease classification by Brindha Subburaj, Rohan M, Samhruth Ananthanarayanan, Daehan Won

“…Most computerized methods involve some form of Deep Learning algorithms and models to automate the detection process. …”
Get full text

Radiomics analysis of thoracic vertebral bone marrow microenvironment changes before bone metastasis of breast cancer based on chest CT by Hao-Nan Zhu, Yi-Fan Guo, YingMin Lin, Zhi-Chao Sun, Xi Zhu, YuanZhe Li

“…Multiple machine learning algorithms were utilized to construct various radiomics models for predicting the risk of bone metastasis, and the model with optimal performance was integrated with clinical features to develop a nomogram. …”
Get full text