Frontiers1d
Neuromorphic and Deep Learning Paradigms for Neural Data Interpretation and Computational Neuroscience
The integration of neuromorphic computing and deep learning is revolutionizing computational neuroscience, offering new methods for interpreting complex ...
GitHub14d
convolutional-neural-networks
This project leverages deep learning to identify crop diseases from images. Built with TensorFlow, the app allows users to upload crop images and predicts the disease. It features a user-friendly ...
IEEE17d
Effective Probabilistic Neural Networks Model for Model-based Reinforcement Learning USV
In this article, a novel probabilistic MBRL approach, probabilistic neural networks model predictive control (PNMPC) is proposed to tackle this issue. With an iterative learning framework, PNMPC ...
Post-Courier25d
Lessons from abroad: PNG explores electricity reform models
Papua New Guinea (PNG) is on the verge of an electricity crisis characterized by low electricity access levels, unreliable and curtailed electricity supply, uncompetitive electricity tariffs, and a ...
devdiscourse25d
Adani Total Gas Expands CNG and PNG Networks Amidst Robust Financial Growth
The company now boasts a total of 13,082 Inch Km of steel pipeline network. During the quarter, the combined volume of CNG and PNG rose to 257 MMSCM, marking a 15% year-on-year increase. Revenue from ...
Business Insider25d
DeepSeek's cheaper models and weaker chips call into question trillions in AI infrastructure spending
Related stories Its smaller size comes in part by using a different architecture than ChatGPT, called a "mixture of experts." The model has pockets of expertise built in, which go into action when ...
IEEE29d
Obstacle Avoidance in a Crowd with a Plastic Recurrent Mushroom Body Model
While conventional spiking neural ... networks (SNNs) provide low power consumption, they often lack of sufficient long-term memory capabilities. To address this, we propose the Plastic Recurrent ...
techxplore29d
Neural networks model improves machine vision and object detection under low-light conditions
The paper is published in the journal Image and Vision Computing. "The use of neural networks in the model allows us to detect this type of marker in a more flexible way, solving the problem of ...