Diabetic Sensorimotor Polyneuropathy Severity Classification Using Adaptive Neuro Fuzzy Inference System by Fahmida Haque (16896489)

“…Early detection and intelligent classification tools for DSPN can allow correct diagnosis and treatment of painful diabetic neuropathy as well as a timely intervention to prevent foot ulceration, amputation, and other diabetic complications. …”

The automation of the development of classification models and improvement of model quality using feature engineering techniques by Sjoerd Boeschoten (17347045)

“…<p>Recently pipelines of machine learning-based classification models have become important to codify, orchestrate, and automate the workflow to produce an effective machine learning model. …”

Novel Classification System for Classifying Cognitive Workload Levels under Vague Visual Stimulation by Mahmoud, Rwan Adil Osman

“…This is followed by variable selection using stepwise regression and multiclass linear classification. The presented method achieved an average classification accuracy of 93.4%. …”
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Classification of Common Partial Discharge Types in Oil-Paper Insulation Using Acoustic Signals by Harbaji, Mustafa

“…A Master of Science thesis in Electrical Engineering by Mustafa Harbaji entitled, "Classification of Common Partial Discharge Types in Oil-Paper Insulation Using Acoustic Signals," submitted in February 2014. …”
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Hybrid Classification Approach Utilizing DenseUNet+ for Diabetic Macular Edema Disorder Detection by Abualigah, Laith

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GENERALIZABLE AND SELECTIVE 2D/3D DEEP-MODEL FOR MULTI-VIEW OBJECT CLASSIFICATION by unknown

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Explainable Deep Learning Based Viral Sequence Classification and Potential Threat Identification for Biosecurity Surveillance by unknown

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ADAPTIVE FUZZY LOGIC BASED FRAMEWORK FOR HANDLING IMPRECISION AND UNCERTAINTY IN PATTERN CLASSIFICATION OF BIOINFORMATICS DATASETS by Rasheed, Zeehasham

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Group Classification and Symmetry Reductions for a Class of Nonlinear Poisson Equations on the Line and Certain Surfaces by unknown

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An in vitro study of the interactive effect of 24 binary and ternary mixtures from the GHS classification groups by Khalil, C.

“…An in vitro study of the interactive effect of 24 binary and ternary mixtures from the GHS classification groups. ALTEX, 22, 128.…”
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A Terrain classification system for coseismic landslide hazard analysis: Lebanon, a case study by Grant, Alex R.

“…To better assess coseismic landslide hazard on a regional scale a new terrain classification system is proposed. First, the landscape is divided into classes based on possible modes of failure, defining kinematically admissible regions, followed by mode-of-failure specific hazard analyses (strength admissibility) within each region. …”
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Binary Classification of 3D Small-Scale Medical Images Using Video Vision Transformers by Abi Younes, Simon

“…The VesselMNIST3d dataset binary classification experiment was implemented by treating the 3D image as video where the third dimension represents the number of frames. …”
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Dual-stage segmentation and classification framework for skin lesion analysis using deep neural network by Khadija Manzoor (22565369)

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Waste Classification for Sustainable Development Using Image Recognition with Deep Learning Neural Network Models by Meena Malik (17542089)

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Enhancing waste sorting and recycling efficiency: robust deep learning-based approach for classification and detection by Faizul Rakib Sayem (21399890)

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A collection of annotated and harmonized human breast cancer transcriptome datasets, including immunologic classification by Jessica Roelands (7516439)

“…We classified the samples according to different immune based classification systems and integrated this information into the datasets. …”

An Optimized Feature Selection Technique in Diversified Natural Scene Text for Classification Using Genetic Algorithm by Ghulam Jillani Ansari (16896342)

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AttDCT: Attention-Based Deep Learning Approach for Time Series Classification in the DCT Domain by Amine Haboub (22392097)

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Addressing Binary Classification over Class Imbalanced Clinical Datasets Using Computationally Intelligent Techniques by Vinod Kumar (48743)

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CAT-Net: Convolution, attention, and transformer based network for single-lead ECG arrhythmia classification by Md Rabiul Islam (6424796)

“…CAT-Net establishes new benchmarks, achieving 99.14% overall accuracy and 94.69% macro F1 score on 5-class arrhythmia classification in the MIT-BIH dataset and 99.58% accuracy with 96.15% macro F1 score for 3-class classification in the INCART dataset.…”