Results 51 to 60 of about 312,321 (283)
Fixed-Point Performance Analysis of Recurrent Neural Networks
, 2016 Recurrent neural networks have shown excellent performance in many applications, however they require increased complexity in hardware or software based implementations. The hardware complexity can be much lowered by minimizing the word-length of weights
Hwang, Kyuyeon +2 more
core +1 more source
Molecular Oncology, EarlyView.This study integrates transcriptomic profiling of matched tumor and healthy tissues from 32 colorectal cancer patients with functional validation in patient‐derived organoids, revealing dysregulated metabolic programs driven by overexpressed xCT (SLC7A11) and SLC3A2, identifying an oncogenic cystine/glutamate transporter signature linked to ...
Marco Strecker +16 more
wiley +1 more source
Liquid biopsy epigenetics: establishing a molecular profile based on cell‐free DNA
Molecular Oncology, EarlyView.Cell‐free DNA (cfDNA) fragments in plasma from cancer patients carry epigenetic signatures reflecting their cells of origin. These epigenetic features include DNA methylation, nucleosome modifications, and variations in fragmentation. This review describes the biological properties of each feature and explores optimal strategies for harnessing cfDNA ...
Christoffer Trier Maansson +2 more
wiley +1 more source
VGM-RNN: Recurrent Neural Networks for Video Game Music Generation [PDF]
, 2018 The recent explosion of interest in deep neural networks has affected and in some cases reinvigorated work in fields as diverse as natural language processing, image recognition, speech recognition and many more.
Mauthes, Nicolas
core +1 more source
Two-Stream RNN/CNN for Action Recognition in 3D Videos
, 2018 The recognition of actions from video sequences has many applications in health monitoring, assisted living, surveillance, and smart homes. Despite advances in sensing, in particular related to 3D video, the methodologies to process the data are still ...
Ali, Haider +2 more
core +1 more source
Strength through diversity: how cancers thrive when clones cooperate
Molecular Oncology, EarlyView.Intratumor heterogeneity can offer direct benefits to the tumor through cooperation between different clones. In this review, Kuiken et al. discuss existing evidence for clonal cooperativity to identify overarching principles, and highlight how novel technological developments could address remaining open questions.
Marije C. Kuiken +3 more
wiley +1 more source
Ultra-low latency recurrent neural network inference on FPGAs for physics applications with hls4ml
Machine Learning: Science and Technology, 2023 Recurrent neural networks have been shown to be effective architectures for many tasks in high energy physics, and thus have been widely adopted.
Elham E Khoda +12 more
doaj +1 more source
, 2018 Recurrent neural networks can learn complex transduction problems that require maintaining and actively exploiting a memory of their inputs. Such models traditionally consider memory and input-output functionalities indissolubly entangled. We introduce a
Bacciu, Davide +2 more
core +1 more source
Potential therapeutic targeting of BKCa channels in glioblastoma treatment
Molecular Oncology, EarlyView.This review summarizes current insights into the role of BKCa and mitoBKCa channels in glioblastoma biology, their potential classification as oncochannels, and the emerging pharmacological strategies targeting these channels, emphasizing the translational challenges in developing BKCa‐directed therapies for glioblastoma treatment.
Kamila Maliszewska‐Olejniczak +4 more
wiley +1 more source
Real-time classification of hand movements as a basis for intuitive control of grasp neuroprostheses
Current Directions in Biomedical Engineering, 2020 This paper reports on the evaluation of recurrent and convolutional neural networks as real-time grasp phase classifiers for future control of neuroprostheses for people with high spinal cord injury.
Amelin Dmitry +6 more
doaj +1 more source