Artificial neural networks
Research from the Fifth Affiliated Hospital of Sun Yat-sen University in Zhuhai, People's Republic of China, has made significant strides in the non-invasive grading of cervical spinal stenosis using deep learning convolutional neural network algorithms. The study, which utilized a dataset of 954 patients with cervical spine magnetic
Artificial neural networks
Researchers at the Universidad Nacional del Altiplano in Peru have developed a novel approach to monitoring rainbow trout (Oncorhynchus mykiss) using deep learning-based semantic image segmentation. This breakthrough technology enables accurate size estimations and health monitoring, paving the way for sustainable aquaculture practices. The study employed two deep learning architectures,
Artificial neural networks
Burn injuries trigger substantial inflammation, complicating wound healing and potentially leading to severe systemic complications. Understanding the immune response to burns is crucial for improving treatment. Researchers from the University of Amsterdam have developed a novel approach using neural networks to predict cytokine concentrations over time and space, which can
Artificial neural networks
Investigators at the Chinese Academy of Sciences have developed a novel biomimetic visual information spatiotemporal encoding method based on improved delayed phase encoding. This method has shown significant potential in integrating in vitro biological neural networks (BNNs) with robotic systems for information processing and adaptive learning in practical tasks. The
Artificial neural networks
Researchers have made significant strides in the field of connectomics by introducing a new framework that enables the accurate mapping of the brain's intricate wiring diagram. This framework, which reasons over global neuron shape, has outperformed existing algorithms in two demanding connectomics tasks: proofreading segmentation errors and classifying
Artificial neural networks
Neuromorphic computing, a rapidly emerging field that draws inspiration from the brain, has made significant strides in recent years. Researchers at Tsinghua University, led by Yifei Yang, have made a groundbreaking discovery that challenges traditional understanding of neural networks. According to a recent study published in the journal Neuromorphic Computing
Artificial neural networks
Researchers have developed a series of deep neural networks that enable automatic non-rigid registration and cell identification in complex cellular tissues. The networks, trained in the context of freely moving and deforming invertebrate nervous systems, demonstrate high accuracy in aligning neurons over time and annotating cell types. The technology has
Artificial neural networks
Samsung Electronics has been assigned a patent for a low-power change-based neural network inference technique for image processing, developed by four inventors: Ishay Goldin, Yonatan Dinai, Ran Vitek, and Michael Dinerstein. The patented technique enables high accuracy computer vision and image processing with decreased system resource requirements. One or more
Artificial neural networks
Samsung Electronics Co., Ltd. has been assigned a patent for an electronic apparatus designed to process images using artificial intelligence. The device includes a memory that stores a neural network model trained to transfer the style of an image, and a processor that performs various image processing operations based on
Artificial neural networks
A team of researchers from Tsinghua University in Beijing, China, has made a significant breakthrough in estimating anthropogenic CO2 emissions in the country. Using remote sensing measurements and a neural network approach, they have developed a more accurate method to estimate CO2 emissions, which is crucial for effective climate change
Artificial neural networks
Research conducted by the Seoul National University Science & Technology has found that Large Language Models (LLMs) pose significant data security risks, particularly in Internet of Things (IoT) environments. The study, published in Computer Networks, highlights the vulnerabilities of LLMs to adversarial attacks, data poisoning, and privacy breaches. The research
Artificial neural networks
Researchers from IMT Atlantique have presented a new deep neural network watermarking technique, RoSe-Mix, designed for black-box settings. According to the study, RoSe-Mix addresses limitations in existing DNN watermarking approaches by integrating key features from two established methods: RoSe, which uses cryptographic hashing to ensure security, and Mixer, which employs
