Are there any biological plausibility aspects to CNN architectures?

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 ... The Machine Learning team at CNN Digital is dedicated to research, build and evaluate Machine Learning and AI capabilities at CNN. The team is comprised of ... Aug 26, 2020 ... Object detection: With CNN, we now have sophisticated models like R-CNN ... machine learning, and artificial intelligence professionals. 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 ... In the study, there are three primary contributions: First, we proposed a classification model to cultivate the performance of classifying of flower images by ... With the increase in computational parallelism and low-power Integrated Circuits (ICs) design, neuromorphic technologies and machine learning algorithms ... ... CNN; Deep neural network; RT-PCR; Computer model. Received: October 27, 2022 ... Machine Learning With Applications, 6, 100138. https://doi.org/10.1016 ... 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 ... Here, the first deep learning (DL) convolutional neural network (CNN) segmentation of multiclass microscale damage in heterogeneous bulk materials is ... 3 From CNN to Faster R-CNN. Deep learning (DL) is a subfield of machine learning which attempts to acquire high-level abstractions in data by utilising ...