How can we develop AI systems that exhibit more human-like perception and reasoning abilities?

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. Jun 28, 2021 ... Fast R-CNN brings feature extraction and region selection into a single machine learning model. Fast R-CNN receives an image and a set of ... 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 ... Apr 3, 2023 ... A CNN works by transforming an input image into a feature map, which is then processed through multiple convolutional and pooling layers to ... Here, the first deep learning (DL) convolutional neural network (CNN) segmentation of multiclass microscale damage in heterogeneous bulk materials is ... Nov 26, 2015 ... The field of machine learning has taken a dramatic twist in recent times, with the rise of the Artificial Neural Network (ANN). These ... 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 ... Apr 12, 2023 ... This paper proposes a machine learning methodology to detect MCI and AD from qEEG time-frequency (TF) images of the subjects in an eyes-closed resting state ( ... We call this approach GRAM-CNN. To automatically label a word, this method uses the local information around a word. Therefore, the GRAM-CNN method does not ... Aug 15, 2022 ... What neural network is appropriate for your predictive modeling problem? It can be difficult for a beginner to the field of deep learning to ...