Automatic writer identification is a common problem in document analysis. State-of-the-art methods typically focus on the feature extraction step with traditional or deep-learning-based techniques. In retrieval problems, re-ranking is a commonly used...
Sparse representation has recently been successfully applied in visual tracking. It utilizes a set of templates to represent target candidates and find the best one with the minimum reconstruction error as the tracking result. In this paper, we propo...
With the rapid growth of the Internet, human daily life has become deeply bound to the Internet. To take advantage of massive amounts of data and information on the internet, the Web architecture is continuously being reinvented and upgraded. From th...
We report on a deep search with the Westerbork Synthesis Radio Telescope towards the galactic anticenter for the 327 MHz hyperfine transition of DI. This is a favorable direction for a search because: (i) the HI optical depth is high due to velocit...
Saturation in deep inelastic scattering (DIS) and deeply virtual Compton scattering (DVCS) is associated with a phase transition between the partonic gas, typical of moderate $x$ and $Q^2$, and partonic fluid appearing at increasing $Q^2$ and decreas...
The fragmentation properties in deep-inelastic scattering (DIS) at HERA are investigated in order to test perturbative QCD and quark fragmentation universality. Selected results for the inclusive single particle distributions and the angular two-pa...
The neutrino deep inelastic scattering (DIS) data is very interesting for global analyses of proton and nuclear parton distribution functions (PDFs) since they provide crucial information on the strange quark distribution in the proton and allow for...
Nanoparticles occur in various environments as a consequence of man-made processes, which raises concerns about their impact on the environment and human health. To allow for proper risk assessment, a precise and statistically relevant analysis of pa...
A new GPS-less, daily localization method is proposed with deep learning sensor fusion that uses daylight intensity and temperature sensor data for Monarch butterfly tracking. Prior methods suffer from the location-independent day length during the e...
Details of Monarch butterfly migration from the U.S. to Mexico remain a mystery due to lack of a proper localization technology to accurately localize and track butterfly migration. In this paper, we propose a deep learning based butterfly localizati...
The international collaboration designing and constructing the Deep Underground Neutrino Experiment (DUNE) at the Long-Baseline Neutrino Facility (LBNF) has developed a two-phase strategy for the implementation of this leading-edge, large-scale scien...
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This paper presents a basic enhancement to the DeSTIN deep learning architecture by replacing the explicitly calculated transition tables that are used to capture temporal features with a simpler, more scalable mechanism. This mechanism uses feedback...
Deep SpatioTemporal Inference Network (DeSTIN) for vision processing (⭐ 35)
Hey Reddit, I’m a student + part-time writer who’s been deep in the trenches testing out different AI humanizers and AI detector bypass tools lately. I write a ton essays, blog posts, even some cl...
Mathematics of Deep Learning, Courant Insititute, Spring 19 (⭐ 277)
Automatic Pill Recognition (APR) systems are crucial for enhancing hospital efficiency, assisting visually impaired individuals, and preventing cross-infection. However, most existing deep learning-based pill recognition systems can only perform clas...
Been diving deep into identity crisis, authenticity, and that weird feeling that you're performing your own life instead of living it. studied research from behavioral psychology, read memoirs from pe...
Been diving deep into identity crisis, authenticity, and that weird feeling that you are performing your own life instead of living it. Studied research from behavioral psychology, read memoirs from p...