In this work, we use similarly separable vectors in separable Hilbert spaces to provide generalized integral results related to majorization, Niezgoda, and Ćebysév type inequalities. Next, we furnish some refinements of these inequalities...
The longstanding Banach–Mazur separable quotient problem asks whether every infinite-dimensional Banach space has a quotient (Banach) space that is both infinite-dimensional and separable. Although it remains open in general, an affirmative ans...
In this work we relax the usual separability assumption made in rate-distortion literature and propose
Remote-sensing time-series data are significant for global environmental change research and a better understanding of the Earth. However, remote-sensing acquisitions often provide sparse time series due to sensor resolution limitations and environme...
Chinese separable words combine lexical integrity with structural separability, but how readers process discontinuous forms during sentence reading remains unclear. Thirty native Chinese speakers read sentences containing discontinuous separable word...
This work motivates and applies operational methodology to simulation of quantum statistics of separable qubit X states. Three operational algorithms for evaluating separability probability distributions are put forward. Building on previous findings...
This study aims to achieve an efficient time-frequency representation of higher-dimensional signals by introducing the notion of a non-separable linear canonical wavelet transform in
In the theory of wavelet frames, the known Daubechies wavelet bases have been generalized to compactly supported (Daubechies-like) wavelet frames, while the known bandlimited Meyer wavelet bases have not been generalized to date. In this study, we wi...
Complex systems are composed of a large number of individual components. Many of these systems are separable, i.e., they can be split into two coupled subsystems: one with foreground components and another with background components. The former leads...
This paper proposes a computational method for the reliability of 2-separable networks. Based on graph theory and probability theory, this method simplifies the calculation process by constructing a network equivalent model and designing correspondin...
In this paper, we prove that every bounded linear operator on a separable Hilbert space has a non-trivial invariant subspace. This answers the well-known invariant subspace problem.
Image inpainting is an active area of research in image processing that focuses on reconstructing damaged or missing parts of an image. The advent of deep learning has greatly advanced the field of image restoration in recent years. While there are m...
The Gaussian-radial-basis function neural network (GRBFNN) has been a popular choice for interpolation and classification. However, it is computationally intensive when the dimension of the input vector is high. To address this issue, we propose a ne...
We propose a separable, reversible watermarking scheme in encrypted images for privacy preservation. The Paillier cryptosystem is used for separable detection and decryption. Users may want to use cloud services without exposing their content. To pre...
In this paper, the structure of a separable convolutional neural network that consists of an embedding layer, separable convolutional layers, convolutional layer and global average pooling is represented for binary and multiclass text classifications...
New families of fourth-order composition methods for the numerical integration of initial value problems defined by ordinary differential equations are proposed. They are designed when the problem can be separated into three parts in such a way that...
Dissolving microneedle (DMN) patches were developed as efficient and patient-friendly transdermal delivery systems for biopharmaceuticals. However, recent studies have confirmed that the efficiency of DMNs to deliver biopharmaceuticals is highly redu...
High security and effectiveness are critical performance metrics in the data transmission process for satellite remote sensing images, medical images, and so on. Previously, the receiver could gain a high-quality cover image (lossy) after decryption...
A dual autoencoder employing separable convolutional layers for image denoising and deblurring is represented. Combining two autoencoders is presented to gain higher accuracy and simultaneously reduce the complexity of neural network parameters by us...
We propose separable reversible data hiding in an encrypted signal with public key cryptography. In our separable framework, the image owner encrypts the original image by using a public key. On receipt of the encrypted signal, the data-hider embeds...
In this paper, we establish the existence and uniqueness of a strong solution to a fractional mean field games system with non-separable Hamiltonians, where the fractional exponent
We give a “naive” (i.e., using no additional set-theoretic assumptions beyond ZFC, the Zermelo-Fraenkel axioms of set theory augmented by the Axiom of Choice) example of a Boolean topological group G without infinite separable pseudocompact subsets h...
The Convolutional Neural Network (CNN) has been used in many fields and has achieved remarkable results, such as image classification, face detection, and speech recognition. Compared to GPU (graphics processing unit) and ASIC, a FPGA (field programm...
This paper introduces a novel capped separable difference of two norms (CSDTN) method for sparse signal recovery, which generalizes the well-known minimax concave penalty (MCP) method. The CSDTN method incorporates two shape parameters and one scale...
Peri-implantitis is a common complication following dental implant placement, which may lead to bone loss and fixation failure. With the conventional fixture, it is difficult to perfectly clear-up the infection. To solve this, we have designed a sepa...
Some characteristics of stationary flows of the Sawada–Kotera system lend themselves to generalization, producing a large class of separable Lagrangian systems with two degrees of freedom. All of these systems come in couples that have the same...
We study the motion of a test particle in a conservative force-field. Our aim is to find three-dimensional potentials with symmetrical properties, i.e.,
Three-dimensional object detection from LiDAR point clouds is essential for autonomous driving, yet existing methods typically rely on costly and extensively annotated datasets. Self-supervised masked autoencoders (MAE) provide a promising alternativ...
An alignment mechanism for producing a sharp tip-separable microneedle device for trans-dermal drug delivery systems has been developed. The needle and base parts were placed on a mechanical precision motion stage to align their central axes. The ove...
Shape classification and segmentation of point cloud data are two of the most demanding tasks in photogrammetry and remote sensing applications, which aim to recognize object categories or point labels. Point convolution is an essential operation whe...
Separable Reversible Data Hiding in Encryption Image (RDH-EI) has become widely used in clinical and military applications, social cloud and security surveillance in recent years, contributing significantly to preserving the privacy of digital images...
Organic and inorganic compounds utilised at different stages of various industrial processes are lost into effluent water and eventually find their way into fresh water sources where they cause devastating effects on the ecosystem due to their stabil...
Numerous variants of the basic deep segmentation model—U-Net—have emerged in recent years, achieving reliable performance across different benchmarks. In this paper, we propose an improved version of U-Net with higher performance and redu...
On edge devices, convolutional neural network (CNN) inference is bottlenecked mainly by memory bandwidth, owing to the frequent memory accesses to feature maps and parameters. To address this challenge, we propose a memory-efficient hardware accelera...
Currently, how to deal with the massive garbage produced by various human activities is a hot topic all around the world. In this paper, a preliminary and essential step is to classify the garbage into different categories. However, the mainstream wa...
At present, ResNet and DenseNet have achieved significant performance gains in the field of finger-vein biometric recognition, which is partially attributed to the dominant design of cross-layer skip connection. In this manner, features from multiple...
Hyperspectral image classification remains challenging because robust recognition requires preserving spatial–spectral coupling, extracting complementary spectral and spatial cues, and fusing heterogeneous features without excessive redundancy....
Transdermal microneedle systems have received great attention due to their minimally invasive way of delivering biomolecules through the skin with reduced pain. However, designing high-strength separable microneedles, which enable easy skin penetrati...
Although hyperspectral data provide rich feature information and are widely used in other fields, the data are still scarce. Training small sample data classification is still a major challenge for HSI classification based on deep learning. Recently,...
The purpose of this study was to develop a new pediatric acuity chart that can assess the minimum separation threshold by incorporating the minimum separation threshold into the picture. To overcome the design limitations of the Landolt ring, two des...
Facing the complex marine environment, it is extremely challenging to conduct underwater acoustic target feature extraction and recognition using ship-radiated noise. In this paper, firstly, taking the one-dimensional time-domain raw signal of the sh...
The increased volume of heavy vehicles and use of de-icing agents on concrete bridge decks accelerates the deterioration of these structures. Therefore, the rapid replacement of these structures has attracted considerable attention, with prefabricate...
In the electrochemical machining (ECM) of variable-pitch internal helical grooves, a conventional integral cathode is subject to a kinematic constraint: the working teeth are rigidly fixed to the cathode body and therefore cannot follow a helix angle...
As cloud computing becomes popular, the security of users’ data is faced with a great threat, i.e., how to protect users’ privacy has become a pressing research topic. The combination of data hiding and encryption can provide dual protect...
Vision is an important way for unmanned mobile platforms to understand surrounding environmental information. For an unmanned mobile platform, quickly and accurately obtaining environmental information is a basic requirement for its subsequent visual...
Depthwise separable convolution (DSC) significantly reduces parameter and floating operations with an acceptable loss of accuracy and has been widely used in various lightweight convolutional neural network (CNN) models. In practical applications, ho...
Computer vision applications require high-quality reproductions of original images, typically demanding complex models with many trainable parameters and floating-point operations. This increases computational load and restricts deployment on resourc...
Replacing 2D-convolution operations by depth-wise separable time and frequency convolutions greatly reduces the number of parameters while maintaining nearly equivalent performances in the context of acoustic scene classification. In our experiments,...
The integrated electronic nose (e-nose) design, which integrates sensor arrays and recognition algorithms, has been widely used in different fields. However, the current integrated e-nose system usually suffers from the problem of low accuracy with s...
Bacterial recognition and classification play a vital role in diagnosing disease by determining the presence of large bacteria in the specimens and the symptoms. Artificial intelligence and computer vision widely applied in the medical domain enable...
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