Stress Classification Using Photoplethysmogram-Based Spatial and Frequency Domain Images حسب Sami Elzeiny (16891521)

"…By combining 20% of the samples collected from test subjects into the training data, the calibrated generic models’ accuracy was improved and outperformed the generic performance across both the spatial and frequency domain images. The average classification accuracy of 99.6%, 99.9%, and 88.1%, and 99.2%, 97.4%, and 87.6% were obtained for the training set, validation set, and test set, respectively, using the calibrated generic classification-based method for the series of inter-beat interval (IBI) spatial and frequency domain images. …"

Drone/Bird Classification Based on Features of Tracks Trajectories حسب Kengeskanov, Maksat

"…This paper presents the outcome of several machine learning techniques used for the task of bird/drone classification based on their tracks. Instead of using static images, the dynamics and features extracted from the trajectories captured in videos are used to provide a more accurate and reliable recognition task. …"
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Active Learning Based Federated Learning for Waste and Natural Disaster Image Classification حسب Lulwa Ahmed (16869936)

"…Promising results are obtained on both applications resulting in comparable results against the best-case scenario where each sample is manually analyzed and annotated (Baseline 1), and improvement of 3.1% and 4% with best methods respectively over the training sets with irrelevant images on natural disaster and waste classification datasets (Baseline 2).…"

Image-CNN Based Process Control of Profile حسب Zeinab, Zeinab Jihad

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Feature modeling using polynomial classifiers and stepwise regression حسب Shanableh, Tamer

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Thermal Change Index-Based Diabetic Foot Thermogram Image Classification Using Machine Learning Techniques حسب Amith Khandakar (14151981)

"…The multilayer perceptron (MLP) classifier along with the features extracted from thermogram images showed an accuracy of 90.1% in multi-class classification, which outperformed the literature-reported performance metrics on this dataset.…"

A Convolutional Neural Network-Based Framework for Classification of Protein Localization Using Confocal Microscopy Images حسب Sonam Aggarwal (16904763)

"…Hence, this study aims to develop a deep learning-based system for the multi-label classification of HPA. …"

Salak Image Classification Method Based Deep Learning Technique Using Two Transfer Learning Models حسب Theng, Lau Wei

"…The size, shape, skin color, sweetness or even flesh color will be different depending on the cultivar. Thus, classification of salak based on their cultivar become a daily job for the fruit farmers. …"
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Markisa/Passion Fruit Image Classification Based Improved Deep Learning Approach Using Transfer Learning حسب Abdo, Ahmed

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Deep Learning-Based Classification of Chest Diseases Using X-rays, CT Scans, and Cough Sound Images حسب Hassaan Malik (10486121)

"…Therefore, we designed a novel deep learning (DL)-based chest disease detection network (DCDD_Net) that uses a CXR, CT scans, and cough sound images for the identification of nine different types of chest diseases. …"

FPGA-based Parallel Hardware Architecture for Real-time Object Classification حسب Qasaimeh, Murad Mohammad

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Kernel-Ridge-Regression-Based Randomized Network for Brain Age Classification and Estimation حسب Raveendra Pilli (21633287)

"…In this study, a brain age classification and estimation framework is proposed using structural magnetic resonance imaging (sMRI) scans, a 3-D convolutional neural network (3-D-CNN), and a kernel ridge regression-based random vector functional link (KRR-RVFL) network. …"

Advancing crop classification in smallholder agriculture: A multifaceted approach combining frequency-domain image co-registration, transformer-based parcel segmentation, and Bi-LSTM for crop classification حسب Waleed Khan (9427344)

"…Furthermore a Bidirectional-Long Short-Term Memory-based (Bi-LSTM) deep learning model is developed and trained for crop classification, achieving results with accuracy of more than 94% and 96% for validation sets of two data sets collected in the field, during 2 growing seasons.…"

MEDIC: a multi-task learning dataset for disaster image classification حسب Firoj Alam (14158866)

"…While notable progress has been made using texts, research on exploiting the images remains relatively under-explored. To advance image-based approaches, we propose MEDIC (https://crisisnlp.qcri.org/medic/index.html), which is the largest social media image classification dataset for humanitarian response consisting of 71,198 images to address four different tasks in a multi-task learning setup. …"

Classification and segmentation of kidney MRI images for chronic kidney disease detection حسب Md. Sakib Bin Islam (20494559)

"…It achieved an accuracy of 94.38% in distinguishing between healthy and CKD cases in kidney MRI image classification. Moreover, the pretrained models Densenet201 and VGG19, as well as the ViT-based models EfficientNet_b1 and tf_mobilenetv3_large_075, demonstrate remarkable sensitivity and accuracy while compared to identifying kidney MRI images which highlights the effectiveness of deep learning architectures in identifying diseases. …"

Lung cancer medical images classification using hybrid CNN-SVM حسب Abdulrazak Yahya Saleh (18520026)

"…This paper presents an image classification method based on the hybrid Convolutional Neural Network (CNN) algorithm and Support Vector Machine (SVM). …"

Automated detection of posterior urethral valves in voiding cystourethrography images: A novel AI-Based pipeline for enhanced diagnosis and classification حسب Saidul Kabir (15302407)

"…Traditional diagnosis relies on subjective interpretation of imaging techniques. This study aimed to automate and increase accuracy of PUV detection in voiding cystourethrography (VCUG) images using an AI-based pipeline. …"

An Exemplar Pyramid Feature Extraction Based Alzheimer Disease Classification Method حسب Heba Soliman Zaina (16904787)

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

An Integrated Design for Classification and Localization of Diabetic Foot Ulcer Based on CNN and YOLOv2-DFU Models حسب Javaria Amin (14557730)