Results 31 to 40 of about 1,256,851 (285)
LSH-GAN enables in-silico generation of cells for small sample high dimensional scRNA-seq data
Communications Biology, 2022 LSH-GAN is a locality-sensitive hashing based generative adversarial model that can produce realistic cell samples from small sample single-cell scRNA-seq data.
Snehalika Lall +2 more
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Fully Connected Hashing Neural Networks for Indexing Large-Scale Remote Sensing Images
Mathematics, 2022 With the emergence of big data, the efficiency of data querying and data storage has become a critical bottleneck in the remote sensing community. In this letter, we explore hash learning for the indexing of large-scale remote sensing images (RSIs) with ...
Na Liu +5 more
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Winning algorithms in BCI Controlled Robot Contest in World Robot Contest 2022: BCI Turing Test
Brain Science Advances, 2023 The Turing Test is a method of testing whether a machine has human intelligence. A novel brain–computer interface (BCI) Turing Test was proposed in the BCI Controlled Robot Contest in World Robot Contest 2022.
Hangjie Yi +4 more
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Escaping from American intelligence : culture, ethnocentrism and the Anglosphere [PDF]
, 2012 The United States and its closest allies now spend over $100 billion a year on intelligence. Ten years after 9/11, the intelligence machine is certainly bigger - but not necessarily better.
Aldrich, Richard J., Kasuku, John
core +1 more source
DeepCXray: Automatically Diagnosing Diseases on Chest X-Rays Using Deep Neural Networks
IEEE Access, 2018 The automatic detection of diseases in images acquired through chest X-rays can be useful in clinical diagnosis because of a shortage of experienced doctors.
Xiuyuan Xu +3 more
doaj +1 more source
Making AI Meaningful Again [PDF]
, 2021 Artificial intelligence (AI) research enjoyed an initial period of enthusiasm in the 1970s and 80s. But this enthusiasm was tempered by a long interlude of frustration when genuinely useful AI applications failed to be forthcoming.
Landgrebe, Jobst, Smith, Barry
core
Computability and human symbolic output [PDF]
, 2013 This paper concerns “human symbolic output,” or strings of characters produced by humans in our various symbolic systems; e.g., sentences in a natural language, mathematical propositions, and so on.
Megill, Jason, Melvin, Tim
core +4 more sources
AULoRA: Anomaly Understanding With Low-Rank Adaptation for Zero-Shot Anomaly Detection
IEEE AccessZero-Shot Anomaly Detection (ZSAD) aims to identify anomalies in unseen categories or scenarios. Recently, Vision-Language Models (VLMs), most notably CLIP, have been utilized to enhance anomaly detection performance.
Seunghyun Oh +3 more
doaj +1 more source
Cyber Threat Intelligence : Challenges and Opportunities
, 2018 The ever increasing number of cyber attacks requires the cyber security and forensic specialists to detect, analyze and defend against the cyber threats in almost realtime.
Conti, Mauro +2 more
core +1 more source
A Roadmap Towards Machine Intelligence [PDF]
, 2018 The development of intelligent machines is one of the biggest unsolved challenges in computer science. In this paper, we propose some fundamental properties these machines should have, focusing in particular on communication and learning. We discuss a simple environment that could be used to incrementally teach a machine the basics of natural-language ...
Tomás Mikolov +2 more
openaire +2 more sources