Comparison between ILSTM and machine learning-based algorithms in binary classification. by Asmaa Ahmed Awad (16726315)

Comparison between ILSTM and deep learning-based algorithms in binary classification. by Asmaa Ahmed Awad (16726315)

MSE for ILSTM algorithm in binary classification. by Asmaa Ahmed Awad (16726315)

“…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …”

Several loop patterns found in binary code. by Alba Pedro-Zapater (8600382)

Optical Assessment of Tear Glucose by Smart Biosensor Based on Nanoparticle Embedded Contact Lens by Hee-Jae Jeon (4614121)

“…Additionally, we propose an image processing algorithm that automatically optimizes the measurement accuracy even in the presence of image blurring, possibly caused by breathing, subtle movements, and eye blinking. …”

Optical Assessment of Tear Glucose by Smart Biosensor Based on Nanoparticle Embedded Contact Lens by Hee-Jae Jeon (4614121)

“…Additionally, we propose an image processing algorithm that automatically optimizes the measurement accuracy even in the presence of image blurring, possibly caused by breathing, subtle movements, and eye blinking. …”

<i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

Random forest model performs better than support vector machine algorithms and when it primarily uses spontaneous photopic ERG of 60-s duration in humans. by Ramsés Noguez Imm (6658637)

Example of simulated calcium imaging dataset. by Virgil Christian Garcia Castillo (19688355)

“…In this study, we report an ROI selection method using a series of adaptive binarizations with a gaussian method and morphological image processing. The parameters for each operation such as the kernel size, sigma and footprint size were optimized. …”

Probability density of each bin of accuracy. by Virgil Christian Garcia Castillo (19688355)

“…In this study, we report an ROI selection method using a series of adaptive binarizations with a gaussian method and morphological image processing. The parameters for each operation such as the kernel size, sigma and footprint size were optimized. …”

ROI masks generated when using 2.5 σ1. by Virgil Christian Garcia Castillo (19688355)

UK Biobank data wrangling statistics and results. by Simeone Marino (81051)

Spontaneous ERG-based random forest model discriminates control and disease cases in rodent models of obesity and type 1 diabetes and predicts disease evolution in the type 1 diabe... by Ramsés Noguez Imm (6658637)

Image4_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF by Cédric Allier (4180903)

“…The networks have been trained to predict quantitative representation of the cell measurements that can be next translated into measurement lists with a local maxima algorithm. In this article, we discuss the performance and limitations of this novel deep learning-based quantification pipeline in comparison with a standard image processing solution. …”

Image1_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF by Cédric Allier (4180903)

“…The networks have been trained to predict quantitative representation of the cell measurements that can be next translated into measurement lists with a local maxima algorithm. In this article, we discuss the performance and limitations of this novel deep learning-based quantification pipeline in comparison with a standard image processing solution. …”

Image3_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF by Cédric Allier (4180903)

“…The networks have been trained to predict quantitative representation of the cell measurements that can be next translated into measurement lists with a local maxima algorithm. In this article, we discuss the performance and limitations of this novel deep learning-based quantification pipeline in comparison with a standard image processing solution. …”

Image2_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF by Cédric Allier (4180903)

“…The networks have been trained to predict quantitative representation of the cell measurements that can be next translated into measurement lists with a local maxima algorithm. In this article, we discuss the performance and limitations of this novel deep learning-based quantification pipeline in comparison with a standard image processing solution. …”

Optimal Timings Codebook.xlsx by Emma Spillane (11249121)

DataSheet1_CNN-Based Cell Analysis: From Image to Quantitative Representation.pdf by Cédric Allier (4180903)

“…The networks have been trained to predict quantitative representation of the cell measurements that can be next translated into measurement lists with a local maxima algorithm. In this article, we discuss the performance and limitations of this novel deep learning-based quantification pipeline in comparison with a standard image processing solution. …”

Optimal Time Intervals of Breech Births Dataset by Emma Spillane (11249121)