What is a confusion matrix?

Jan 22, 2025 ... A breakthrough in building models for image classification came with the discovery that a convolutional neural network (CNN) could be used ... Mar 25, 2023 ... In this paper, we compared and explored the two methodologies on the DEMoS dataset consisting of 8869 audio files of 58 speakers in different emotional states. In this paper, three prediction algorithms have been proposed which will predict the protein secondary structure based on machine learning. This paper presents “EspiNet V2” a Deep Learning model, based on the region-based detector Faster R-CNN. The model is used for the detection of motorcycles ... Jun 10, 2020 ... ... machine learning WorldView-2 results,. (d) a Sentinel-2 image of Study Site 1, (e) CNN deep learning Sentinel results, and (f) RF machine. Aug 1, 2019 ... ... CNN), which is kind of deep learning. Mask R-CNN technique is a recently proposed algorithm not only for object detection and object ... Jun 27, 2017 ... The convolution in a CNN is going to be the kernel g of which we will learn some weights in order to extract the information we need and then perhaps apply an ... Sep 25, 2023 ... Region-based Convolutional Neural Network (R-CNN) is a type of deep learning architecture used for object detection in computer vision tasks. Mar 28, 2024 ... SANS-CNN is designed specifically for astronaut ophthalmic health and demonstrates robust detection of SANS-like conditions when compared to ... Feb 20, 2020 ... LeNet-5. LeNet-5 architecture is perhaps the most widely known CNN architecture. It was created by Yann LeCun in 1998 and widely used for ...