Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 22 for “"ResNet50"”.
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Sensitivity of Feedforward Neural Networks to Harsh Computing Environments
… to be on par with random guessing. VGG16, ResNet50, and InceptionV3 were also tested for their robustness. ResNet50 and InceptionV3 were both more robust than VGG16. This could be due to their use of Batch Normalization or the fact that ResNet50 and InceptionV3 both use shortcut connections …
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Evaluating deep learning for enhanced breast cancer diagnosis: a comparative analysis of CNN architectures
… model, alongside well-established models like ResNet50 and EfficientNetB0, was developed and evaluated for its accuracy in predicting benign and malignant breast cancer subtypes. The results demonstrated that while the custom CNN achieved an accuracy of 65% for malignant and 67% for benign …
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Automated Visual Inspection of Lyophilized Products via Deep Learning and Autoencoders
… neural network architectures including VGG16 and ResNet50. We compare results from training these architectures from scratch to results using fine-tuning of pretrained variants of the models, and find that the pretrained variants not only help improve accuracies, but help the model learn the …
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Satellite Image Analysis and Sidewalk Classification using Deep Learning Models
… using pretrained CNN models including VGG16 and ResNet50. I extended these models by adding custom layers at the top of pretrained layers, employing various techniques to improve the classification accuracy.</p> <p>The dataset comprises 4,731 images of sidewalk based on occlusion levels, …
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Machine Learning Methods for Personalized Treatment Response Characterization Using Clinical Care Brain MRI and Non-Imaging Data in Multiple Sclerosis
… on a top-ranking convolutional neural network, ResNet50, for predicting 2-year treatment response using Clinical Only, MRI Only, or Combined input. To handle class imbalance, this study applied a unique dural-labeling system between training and testing. Overall results showed the robustness of …
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Deep Learning for Early Detection, Identification, and Spatiotemporal Monitoring of Plant Diseases Using Multispectral Aerial Imagery
… convolutional neural networks (VGG16, VGG19, ResNet50, Inception V3, and Xception) in classifying crop diseases for apples, grapes, and tomatoes. The results of the study show that the best performing crop-disease classification models were those trained on the VGG16 network, while those …
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Enhancing detection of cervical cancer through deep learning: a comparative study of histological image-based algorithms
… I investigate the application of DL models—ResNet50, SqueezeNet, EfficientNet, and a Visual Prompting Model—for classifying cervical cells using histopathological images. I conduct a comparative analysis to evaluate these models based on accuracy, sensitivity, specificity, and …
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Object Detection and Size Determination of Pineapple Fruit at a Juicing Factory
… detector made use of MS COCO starting weights, a ResNet50 CNN backbone, and horizontal flipping data augmentation during the training process. This model (Model 4: COCO Fliplr Res50) achieved an average precision of 91.4% on the validation set and an average precision of 90.1% on the test set, and …
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Multi-modal Multi-Level Neuroimaging Fusion with Modality-Aware Mask-Guided Attention and Deep Canonical Correlation Analysis to Improve Dementia Risk Prediction
… modality-specific feature extraction using ResNet50 backbones, followed by middle fusion enhanced with a Modality-Aware Mask-Guided Attention (MAMGA) mechanism. To address missing modalities and inter-modal misalignment, the model incorporates Random Modality Masking and Deep Canonical …
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Speech-Based Artificial Intelligence Emotion Biomarkers in Frontotemporal Dementia
… at the University of Melbourne. We develop two ResNet50 models to classify FTD vs healthy elderly controls using spectrograms of speech samples: 1) a naive model, and 2) a model that was pretrained on an emotions speech dataset. We compare the validation accuracies of the two models on different …
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Deep CNN-Based Automated Optical Inspection for Aerospace Components
… Second, deep CNN-based models, such as improved ResNet50 and MobileNetV2 architectures are trained on ACMID datasets. Third, an efficient defect detection technique that combines the features of deep learning and classical machine learning model is proposed for ACMID dataset. To assess the …
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Development of a Fully Automated Al System for Skeletal Maturity Assessment Using Cone Beam CT
… assessment, the highest performing pipeline was ResNet50 with knowledge distillation, which achieved an accuracy of 88.54%. Our results demonstrate the development of the first deep learning framework for SOS classification. In addition, this study introduces a novel pipeline for CVM …
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Semi-Supervised Transfer Learning for medical images as an alternative to ImageNet Transfer Learning
… the standard ImageNet architectures, we evaluate ResNet50 and Inception-v3, which have both been used extensively in medical deep learning applications. Our proposed method outperforms both standard ImageNet models on the target task. These results demonstrate that learning features from …
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Investigating automated bird detection from webcams using machine learning
… Faster R-CNN in combination with MobileNet-V2, ResNet50, ResNet101, ResNet152, and Inception ResNet-V2 feature extractors were studied and evaluated. Through the use of transfer learning, all the models were initialized using weights pre-trained on the MS COCO (Microsoft Common Objects in …
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Obstacle and Change Detection Using RGB Cameras
… such as MobileNetV3-large, EfficientNetB3, ResNet50, and DenseNet121, and their feature-level ensembled model, matched using cosine similarity in threadpooling architecture for dataset reduction and detection. The performance is evaluated by accuracy, precision, recall, F1-score, …
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Advancing Explainability in Multi-Label Classification for Tomato Disease Detection Using Machine Learning Interpretability Techniques
… 93.75% for EfficientNetB0, and 87.50% for ResNet50, our proposed models outperform earlier research on the same dataset, demonstrating a notable increase in accuracy over previous models. Additionally, we implemented three explainable AI techniques to enhance the transparency and …
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Estimation and Optimization in Online Marketplaces
… optimize the impact of photo layout. We apply Resnet50, a convolutional neural network model, to build two separate, supervised learning models to evaluate the image quality and room types posted by Airbnb hosts. Then, we characterize the overall impacts of photo layout by the room type, photo …
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Efficient Network Systems Design for Machine Learning
… Trio-ML on a testbed with three real DNN models (ResNet50, DenseNet161, and VGG11) to demonstrate its effectiveness in mitigating stragglers while performing in-network aggregation. Our evaluations show that when stragglers occur in the cluster, Trio-ML outperforms today's state-of-the-art …
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Study on speech emotion recognition based on deep learning
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-12-01
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The Detection of Vegetation Species in Remote Sensing Imaging
… neural networks (Google-NET, VGG16, VGG19, ResNET50, ResNET101) and shallow convolutional neural networks have been trained to five different classes of ROI images including unknown range: wheat, black grass, road, and bushes. Finally, the conclusions drawn from this research and makes …
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