Zobrazeno 1 - 10
of 1 752
pro vyhledávání: '"Wicaksana A"'
Publikováno v:
Frontiers of Nursing, Vol 10, Iss 4, Pp 427-436 (2023)
To identify the level of dietary adherence for particular foods and determine which are challenging for patients with diabetes in Indonesia, as well as the associated factors.
Externí odkaz:
https://doaj.org/article/4cef06cfb1284a289b9ec5ca8259659b
Publikováno v:
Frontiers of Nursing, Vol 9, Iss 3, Pp 255-261 (2022)
The aim of this study was to evaluate health-promoting behaviors among hypertensive patients with and without comorbidities.
Externí odkaz:
https://doaj.org/article/ea771ebb5776403a946a5e007546bcc1
Autor:
Minhas, Mishal Fatima, Putra, Rachmad Vidya Wicaksana, Awwad, Falah, Hasan, Osman, Shafique, Muhammad
To adapt to real-world dynamics, intelligent systems need to assimilate new knowledge without catastrophic forgetting, where learning new tasks leads to a degradation in performance on old tasks. To address this, continual learning concept is propose
Externí odkaz:
http://arxiv.org/abs/2410.09218
Convolutional Neural Networks (CNNs), a prominent type of Deep Neural Networks (DNNs), have emerged as a state-of-the-art solution for solving machine learning tasks. To improve the performance and energy efficiency of CNN inference, the employment o
Externí odkaz:
http://arxiv.org/abs/2408.02412
Limited training data and severe class imbalance pose significant challenges to developing clinically robust deep learning models. Federated learning (FL) addresses the former by enabling different medical clients to collaboratively train a deep mode
Externí odkaz:
http://arxiv.org/abs/2407.12446
Autonomous embedded systems (e.g., robots) typically necessitate intelligent computation with low power/energy processing for completing their tasks. Such requirements can be fulfilled by embodied neuromorphic intelligence with spiking neural network
Externí odkaz:
http://arxiv.org/abs/2407.05262
Spiking Neural Networks (SNNs) have shown capabilities for solving diverse machine learning tasks with ultra-low-power/energy computation. To further improve the performance and efficiency of SNN inference, the Compute-in-Memory (CIM) paradigm with e
Externí odkaz:
http://arxiv.org/abs/2407.00641
Recent trends have shown that autonomous agents, such as Autonomous Ground Vehicles (AGVs), Unmanned Aerial Vehicles (UAVs), and mobile robots, effectively improve human productivity in solving diverse tasks. However, since these agents are typically
Externí odkaz:
http://arxiv.org/abs/2404.09331
Autonomous Driving (AD) systems are considered as the future of human mobility and transportation. Solving computer vision tasks such as image classification and object detection/segmentation, with high accuracy and low power/energy consumption, is h
Externí odkaz:
http://arxiv.org/abs/2404.03493
Autor:
Putra, Rachmad Vidya Wicaksana, Marchisio, Alberto, Zayer, Fakhreddine, Dias, Jorge, Shafique, Muhammad
Robotic technologies have been an indispensable part for improving human productivity since they have been helping humans in completing diverse, complex, and intensive tasks in a fast yet accurate and efficient way. Therefore, robotic technologies ha
Externí odkaz:
http://arxiv.org/abs/2404.03325