Search Results for author:
Found 6 papers, 2 papers with code
Texture Extraction Methods Based Ensembling Framework for Improved Classification
Our proposed framework works well on most texture types simultaneously and allows flexibility for additional texture-based methods to be accommodated to achieve better results than existing architectures.
Machine Learning Approaches to Real Estate Market Prediction Problem: A Case Study
Among the four studied machine learning algorithms, XGBoost delivers superior results and robustness of the model compared to other models.
Binary Search and First Order Gradient Based Method for Stochastic Optimization
In deep neural network setup, it handles the problem of vanishing and exploding gradient efficiently.
Housing Market Prediction Problem using Different Machine Learning Algorithms: A Case Study
Developing an accurate prediction model for housing prices is always needed for socio-economic development and well-being of citizens.
Incorporating Image Gradients as Secondary Input Associated with Input Image to Improve the Performance of the CNN Model
In existing CNN architectures, to train the network on given input, only single form of given input is fed to the network.
Overcoming Overfitting and Large Weight Update Problem in Linear Rectifiers: Thresholded Exponential Rectified Linear Units
We will show better performance on the various datasets using neural networks, considering TERELU activation method compared to other activations.
