What are the key hyperparameters that affect the learning rate of a CNN?

Mar 25, 2025 ... We introduce CNN-TumorNet, an innovative method for brain tumor classification utilizing a deep convolutional neural network (CNN) for the ... Jun 27, 2024 ... ... machine learning by regression-based CNN. As a result, the lowest nonlinearity of 0.3% with precision as high as 98.7 is given in our PSD as ... Aug 16, 2024 ... Reinforcement learning. Actor-Critic method · TensorFlow agents. tf ... This tutorial demonstrates training a simple Convolutional Neural Network ... Feb 10, 2020 ... The main novelty of this study was to build a coupled CNN–LSTM model to predict water quality variables. Two traditional machine learning models ... Jan 30, 2023 ... Abstract. In this study, the leaves are classified by various Machine Learning (ML) and Deep Learning (DL) based Convolutional Neural ... Jan 21, 2021 ... In machine learning, each type of artificial neural network is tailored to perform certain sets of tasks. In order to explain these tasks and ... Aug 5, 2022 ... An integrated and hybrid approach based on deep convolutional neural network and machine learning classifiers is proposed for the accurate segmentation and ... Jan 22, 2025 ... A breakthrough in building models for image classification came with the discovery that a convolutional neural network (CNN) could be used ... Sep 30, 2024 ... I'm a CS student and have already studied and implemented "normal" Neural Networks, as well as many other machine learning algorithms, so I have ... What is a Convolutional Neural Network? In machine learning, a classifier assigns a class label to a data point. For example, an image classifier produces a ...