MIT’s researchers have developed an MRI machine in collaboration with a deep learning model, correcting previous MRI technology and enhancing diagnostic accuracy to prevent misdiagnoses, revolutionising the field of medical imaging in diagnostic processes.
Researchers have demonstrated the integration of a deep learning model and CRISPR screens, allowing precise manipulation of gene expression and opening up possibilities for developing novel CRISPR-based therapies.
Deep learning methods help students comprehend artificial intelligence (AI) and how it may tackle complicated issues. Students can use this information to solve real-world challenges in society, economics, and defence.
Deep learning still puzzles researchers due to its complexity; even scientists who build them do not understand everything underneath the shell which has driven an MIT researcher to understand the technology better.
The solution combined with a Wi-Fi signal has helped researchers detect breathing movement and deep learning to analyse any pattern problem and decide whether a particular breathing anomaly occurs.
The deep learning model identifies and quantifies chicken distress calls from natural barn sounds with 97% accuracy will help improve conditions and the welfare of chickens raised on crowded commercial farms.
When it comes to AI, there may not be a more complex set of algorithms than Deep Learning its use has risen more and more among China’s data scientists.
Lensless cameras have applications in augmented reality, virtual reality, security, smart wearables, and robotics where cost, form factor, and weight are major constraints.
Two tech firms under the HK government tech lab launched their solutions – a Platform as superior service (RPass) and a Deep Learning for Advanced Computer Vision SDK (DLACV) solution, respectively.
A novel approach to extract spatial features from metal-binding sites using an energy-based affinity grid map was used. An AI approach based on deep learning is now being developed that will turn raw data to valuable knowledge.
Access to the tech could provide a huge boost for small and medium enterprises that cannot invest in the people needed to do the required technological development.
Dr. Tan shares his vision of the not-too-distant future, with supercomputers built in housing developments and a seamless bench-to-bedside flow dynamically creating precise personalised medical treatments.
OpenGov spoke to Ju Fan, Research Fellow, National University of Singapore, Wei Wang, PhD Student, National University of Singapore, who are working on developing a distributed deep learning platform, Apache SINGA. Apache SINGA is a distributed deep learning platform that entered Apache incubator in March of this year.
“It is almost like there is a magic mechanism inside…developed during the long process of human evolution…What if we can leverage this mechanism to help the computers to learn?”
It would track us, prompt us about what we have to prepare for, suggest materials, pro-actively manage cognitive decay.
MIT PhD student has revolutionised machine learning by offering a framework for scalable data processing, collaborating with the experts, earning acclaim for bridging mathematical theory with practical AI applications.
NUS statisticians have developed a new method using deep learning to accurately estimate low-dimensional structures within complex data, revolutionising data analysis with potential applications in RNA sequencing and biodata analysis.
Embracing and empowering digital transformation through a proactive and continuous learning approach in an increasingly tech-driven world.
The National Security Agency and its federal agency partners have collaborated to release new guidance concerning a cybersecurity risk posed by deepfakes, ensuring the integrity of digital information and safeguarding national security.
Inspired by a movie, MIT researchers developed an innovative technique for controlling autonomous aircraft with AI-based, creating stability and evasion.
Thailand’s Digital Economy Promotion Agency is actively promoting digital skills development, facilitating online learning platforms, and fostering collaborations to drive AI implementation and enhance the country’s competitiveness in the digital technology sector.
Researchers have developed machine learning algorithms to design novel proteins with desired structural properties, potentially creating sustainable materials with tailored properties, such as wrappings to keep food fresher.
AI was used to create a benchmark for measuring brain atrophy in neurodegenerative diseases by producing synthetic MRI images, enabling accurate assessment and comparison of measurement methods; the synthetic dataset images are publicly available for further research.
Researchers from the United States developed a unique model that maps developmental pathways to tumour cells, which may disclose the identity of malignancies with unknown origins; and improved the picture generator using artificial intelligence.
Researchers explore a human speech recognition model based on machine learning and deep neural networks; they calculated how many words per sentence a listener understands using automatic speech recognition.
MIT researchers developed a technique that induces fairness directly into the machine learning model, no matter how unbalanced the training dataset, that can boost the model’s performance on downstream tasks.
Researchers have discovered an electronic chip that can be reprogrammed on demand may enable artificial intelligence to learn more continuously as the human brain does.
The KOVIS framework can generalise what it learns from simulated conditions, minimising its need for real-life training data, making it faster and easier to train robots that can perform tasks with unprecedented precision.
By employing a new framework, Chinese researchers developed a new AI programme that is on par with sophisticated human players in a popular card game in which players often deceive and bluff.
MIT researchers have developed a machine learning model that understands the underlying relationships between objects in a scene and can generate accurate images of scenes from text descriptions.
© 2024 OpenGov Asia – CIO Network Pte Ltd.
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