Related papers: Dynamic Pooling Improves Nanopore Base Calling Acc…
A number of recent studies have shown that a Deep Convolutional Neural Network (DCNN) pretrained on a large dataset can be adopted as a universal image description which leads to astounding performance in many visual classification tasks.…
Summary: Raw nanopore signals can be analyzed while they are being generated, a process known as real-time analysis. Real-time analysis of raw signals is essential to utilize the unique features that nanopore sequencing provides, enabling…
The ionic selectivity of nanopores is crucial for the energy conversion based on nanoporous membranes. It can be significantly affected by various parameters of nanopores and the applied fields driving ions through porous membranes. Here,…
Motion sensors embedded in wearable and mobile devices allow for dynamic selection of sensor streams and sampling rates, enabling several applications, such as power management and data-sharing control. While deep neural networks (DNNs)…
Convolutional neural networks (CNN) have achieved impressive performance on the wide variety of tasks (classification, detection, etc.) across multiple domains at the cost of high computational and memory requirements. Thus, leveraging CNNs…
We propose using graphene electrodes with hydrogenated edges for solid-state nanopore-based DNA sequencing, and perform molecular dynamics simulations in conjunction with electronic transport calculations to explore the potential merits of…
In living organisms, information is processed in interconnected symphonies of ionic currents spiking through protein ion channels. As a result of dynamically switching their conductive states, ion channels exhibit a variety of…
Objectives. The aim of this study was to investigate whether a deep convolutional neural network (CNN) with an attention module can detect osteoporosis on panoramic radiographs. Study Design. A dataset of 70 panoramic radiographs (PRs) from…
A hypercomplex representation of DNA is proposed to facilitate comparison of DNA sequences with fuzzy composition. Using hypercomplex number representation, conventional sequence analysis method, such as, dot matrix analysis, dynamic…
Achieving faster execution with shorter compilation time can foster further diversity and innovation in neural networks. However, the current paradigm of executing neural networks either relies on hand-optimized libraries, traditional…
Ionic currents accompanying DNA translocation strongly depend on molarity of the electrolyte solution and the shape and surface charge of the nanopore. By means of the Poisson-Nernst-Planck equations it is shown how conductance is modulated…
Dynamic nuclear polarization (DNP) enhances the intensity of NMR signals by transferring polarization from electron spins to nuclei via microwave irradiation. Pulsed DNP methods offer more control on the spin dynamics than conventional…
Solid state nanopores have emerged as powerful tools for single-molecule sensing, yet the rapid uncontrolled translocation of the molecule through the pore remains a key limitation. We have previously demonstrated that an active…
Most current speech technology systems are designed to operate well even in the presence of multiple active speakers. However, most solutions assume that the number of co-current speakers is known. Unfortunately, this information might not…
Direction of arrival (DoA) estimation of targets improves with the number of elements employed by a phased array radar antenna. Since larger arrays have high associated cost, area and computational load, there is recent interest in thinning…
Modern convolutional neural networks (CNNs) are workhorses for video and image processing, but fail to adapt to the computational complexity of input samples in a dynamic manner to minimize energy consumption. In this research, we propose…
Printed electronics offer ultra-low manufacturing costs and the potential for on-demand fabrication of flexible hardware. However, significant intrinsic constraints stemming from their large feature sizes and low integration density pose…
The explicit neural radiance field (NeRF) has gained considerable interest for its efficient training and fast inference capabilities, making it a promising direction such as virtual reality and gaming. In particular, PlenOctree (POT)[1],…
The rapid increase in symbolic data has underscored the significance of pattern matching and regular expression processing. While nondeterministic finite automata (NFA) are commonly used for these tasks, they are limited to detecting…
Convolution utilizes a shift-equivalent prior of images, thus leading to great success in image processing tasks. However, commonly used poolings in convolutional neural networks (CNNs), such as max-pooling, average-pooling, and…