La principale differenza tra deep learning e machine learning è la struttura dell'architettura della rete neurale sottostante. «Nondeep», i modellitradizionali di machine learningutilizzano reti neurali semplici con uno o due livelli computazionali. I modelli di deep learning utilizzano tre...
deep learning may be applied in cancer diagnosis, prognosis and treatment management. We also assess the current limitations and challenges for the application of deep learning in precision oncology, including the lack of phenotypically rich data and the need for more explainable deep learning models....
Single image dehazing has received a lot of concern and achieved great success with the help of deep-learning models. Yet, the performance is limited by the local limitation of convolution. To address such a limitation, we design a novel deep learning dehazing model by combining the transformer...
deeplearning.ai , By Andrew Ng, All slide and notebook + code and some material. - Forks · RuoyuHua/deeplearning.ai
deeplearning.ai , By Andrew Ng, All slide and notebook + code and some material. - Forks · moqi0311/deeplearning.ai
(Ubuntu 22.04) • AWS GPU AMI TensorFlow 2.16 con apprendimento approfondito (Amazon Linux 2) • AWS GPU AMI di deep learning TensorFlow 2.16 (Ubuntu 20.04) AWS Neurone • Consultate la Guida DLAMI di Neuron Multi-framework DLAMIs Tip Se utilizzi solo un framework di machine learning,...
Vincent P, Larochelle H, Lajoie I, Bengio Y, Manzagol P (2010) A stacked denoising autoencoders: learning useful representations in a deep network with a local denoising criterion pierre-antoine manzagol. J Mach Learn Res 11:3371–3408 MathSciNet MATH Google Scholar Kamilaris A, Prenafeta...
AI-DPAPT: a machine learning framework for predicting PROTAC activity Amr S. Abouzied Bahaa Alshammari Shaymaa E. Kassab Molecular Diversity(2024) Discovery of small molecule degraders for modulating cell cycle Liguo Wang Zhouli Yang Yu Rao ...
What has happened in machine learning lately, and what does it mean for the future of medical image analysis? Machine learning has witnessed a tremendous amount of attention over the last few years. The current boom started around 2009 when so-called deep artificial neural networks began outperfor...
This paper proposes a track and field training state recognition method based on the acceleration sensor and deep learning algorithms. The proposed method uses an acceleration sensor to detect the accurate motion information of the human body in real-time and a deep learning method to process and ...