76 citations · 310 across the 22 of their papers we have counts for
8 papers · 1 filter
On Manifold Hypothesis: Hypersurface Submanifold Embedding Using Osculating Hyperspheres
Benyamin Ghojogh, Fakhri Karray, Mark Crowley
Consider a set of data points in the Euclidean space . This set is called dataset in machine learning and data science. Manifold hypothesis states that the datase…
Deep Learning Approaches for Forecasting Strawberry Yields and Prices Using Satellite Images and Station-Based Soil Parameters
Mohita Chaudhary, Mohamed Sadok Gastli, Lobna Nassar +1
Computational tools for forecasting yields and prices for fresh produce have been based on traditional machine learning approaches or time series modelling. We propose here an alte…
Fisher Discriminant Triplet and Contrastive Losses for Training Siamese Networks
Benyamin Ghojogh, Milad Sikaroudi, Sobhan Shafiei +3
Siamese neural network is a very powerful architecture for both feature extraction and metric learning. It usually consists of several networks that share weights. The Siamese conc…
Backprojection for Training Feedforward Neural Networks in the Input and Feature Spaces
Benyamin Ghojogh, Fakhri Karray, Mark Crowley
After the tremendous development of neural networks trained by backpropagation, it is a good time to develop other algorithms for training neural networks to gain more insights int…
Anomaly Detection and Prototype Selection Using Polyhedron Curvature
Benyamin Ghojogh, Fakhri Karray, Mark Crowley
We propose a novel approach to anomaly detection called Curvature Anomaly Detection (CAD) and Kernel CAD based on the idea of polyhedron curvature. Using the nearest neighbors for…
Theoretical Insights into the Use of Structural Similarity Index In Generative Models and Inferential Autoencoders
Benyamin Ghojogh, Fakhri Karray, Mark Crowley
Generative models and inferential autoencoders mostly make use of norm in their optimization objectives. In order to generate perceptually better images, this short paper…