There are many image resizing techniques, which include scaling, scale-and-stretch, seam carving, and so on. They have their own advantages and are suitable for different application scenarios. Therefore, a universal detection of tampering by image r...
A novel content-aware image resizing mechanism based on composition detection and composition rules is proposed to address the lack of esthetic perception in current content-aware resizing algorithms. A composition detection module is introduced for...
Background: Roux-en-Y gastric bypass (RYGB) is currently one of the most performed bariatric procedures and it is associated with rapid weight loss. However, weight loss failure and weight regain after RYGB occurs in approximately 30% and 3–5%...
Image resizing (IR) has a crucial role in remote sensing (RS), since an image’s level of detail depends on the spatial resolution of the acquisition sensor; its design limitations; and other factors such as (a) the weather conditions, (b) the l...
Granting access to drinking water has been a challenge because 47% of the worldwide population is not connected to a drinking water distribution network in rural settlements. This study aimed to evaluate the contaminant removal efficiency in a conven...
Nowadays, with the increased numbers of video cameras, the amount of recorded video is growing. Efficient video browsing and retrieval are critical issues when considering the amount of raw video data to be condensed. Activity-based video synopsis is...
Introduction: The laparoscopic resizing of the gastric pouch (LPR) has recently been proposed as a revisional technique in the case of weight regain (WR) after gastric bypass procedures. The aim of this study was to report our experience with LPR for...
Mixed-scene holographic 3D display for film and television visual content presentation remains challenging because recorded digital holograms and computer-generated holograms (CGHs) are produced under different numerical and hardware constraints. Dir...
Upcycling recycled carbon fibers recovered from waste carbon composites can reduce the price of carbon fibers while improving disposal-related environmental problems. This study assessed and characterized recycled carbon fibers subjected to sizing tr...
Monocular metric depth estimation models increasingly incorporate camera intrinsics or learn camera-aware representations to recover physically meaningful scales. However, existing camera-aware studies have paid limited attention to a practical deplo...
Most recycling methods remove the essential sizing from reinforcing fibres, and many studies indicate the importance of applying sizing on recycled fibres, a process we will denote here as resizing. Recycled fibres are not continuous, which dissociat...
Structural magnetic resonance imaging (sMRI) is widely used in the clinical diagnosis of diseases due to its advantages: high-definition and noninvasive visualization. Therefore, computer-aided diagnosis based on sMRI images is broadly applied in cla...
Lung segmentation of chest X-ray (CXR) images is a fundamental step in many diagnostic applications. Most lung field segmentation methods reduce the image size to speed up the subsequent processing time. Then, the low-resolution result is upsampled t...
In this work, we report the study of resizing of lead chalcogenide quantum dots, both PbS and PbSe, in the presence of the oleylamine/oleic acid mixture. We demonstrate that the resizing of lead chalcogenide nanocrystals could be performed in aprotic...
This study introduces an efficient graph-based approach for optimal resilience enhancement of existing water distribution networks through the re-sizing of specific pipes. It utilizes modified graph metrics to track the spatial failure propagation re...
Image retargeting is a common computer graphics task which involves manipulating the size or aspect ratio of an image. This task often presents a challenge to the artist or user, because manipulating the size of an image necessitates some degree of d...
Integral imaging is a promising 3D sensing and visualization technique that enables full-parallax and continuous viewpoint reconstruction. However, challenges, such as depth distortion and a limited field-of-view (FoV), can compromise the quality of...
With the development of science and technology, neural networks, as an effective tool in image processing, play an important role in gradual remote-sensing image-processing. However, the training of neural networks requires a large sample database. T...
Rice is a vital crop for global food security, but its production is vulnerable to various diseases. Early detection and treatment of rice diseases are crucial to minimise yield losses. Convolutional neural networks (CNNs) have shown great potential...
The survival probability of persons requiring rescue after large-scale earthquakes or landslides decreases rapidly with time, and nighttime search operations are constrained by limited visibility. Satellite remote sensing enables wide-area observatio...
In medical diagnostics, brain tumor classification remains essential, as accurate and efficient models aid medical professionals in early detection and treatment planning. Deep learning methodologies for brain tumor classification have gained popular...
The practice of Deep Convolution neural networks in the field of medicine has congregated immense success and significance in present situations. Previously, researchers have developed numerous models for detecting abnormalities in musculoskeletal ra...
The layout of water resources and the complex and rational use of them have an important role in the socioeconomic activities of an urban settlement. Transversal hydrotechnical constructions such as weirs reduce the longitudinal connectivity of river...
High-definition (HD) maps for autonomous driving rely on data from mobile mapping systems (MMS), but the high cost of MMS sensors has led researchers to explore cheaper alternatives like low-cost LiDAR sensors. While cost effective, these sensors pro...
Since 2014, Japan has implemented a policy for forming a compact urban structure at a national level through an urban planning technique called a location normalization plan. A residence-induced zone included in the location normalization plan is con...
The interaction between genetic polymorphism and feeding system on milk traits and fatty acid composition was investigated in Modicana cows. Two DGAT1 K232A genotypes (AK and AA) and two feeding regimes, extensive system (EX) with 8 h of grazing with...
The performance of a semantic segmentation model for remote sensing (RS) images pre-trained on an annotated dataset greatly decreases when testing on another unannotated dataset because of the domain gap. Adversarial generative methods, e.g., DualGAN...
Over the past few years, aviation security has turned into a vital domain as foreign object debris (FOD) on the airport paved path possesses an enormous possible threat to airplanes at the time of takeoff and landing. Hence, FOD’s precise ident...
This research presents a time-effective approach for mapping streambed and riparian zone extent from high spatial resolution LiDAR derived products, i.e., digital terrain model, terrain slope and plant projective cover. Geographic object based image...
In this work, we present some techniques applicable to Initial Value Problems when solving a System of Ordinary Differential Equations (ODE). Such techniques should be used when applying adaptive step-size numerical methods. In our case, a Runge-Kutt...
Problem: In the deep image steganography field, the main challenge is to achieve a balance between visual image quality, reliably recovering the message, robustness, and interpretability, especially regarding image distortion because of noise, attack...
Varroa destructor is the most devastating ectoparasite of Apis mellifera, and early detection is critical for colony survival. This study systematically investigated how image preprocessing, model architecture, and feature map resolution jointly affe...
This methodology assesses the accuracy with which remote data characterizes a surface, as a function of Full Width at Half Maximum (FWHM). The purpose is to identify the best remote data that improves the characterization of a surface, evaluating the...
The bird’s-eye view (BEV) method, which is a vision-centric representation-based perception task, is essential and promising for future Autonomous Vehicle perception. It has advantages of fusion-friendly, intuitive, end-to-end optimization and...
SNS providers are known to carry out the recompression and resizing of uploaded images, but most conventional methods for detecting fake images/tampered images are not robust enough against such operations. In this paper, we propose a novel method fo...
The autonomous flight of an unmanned aerial vehicle refers to creating a new flight route after self-recognition and judgment when an unexpected situation occurs during the flight. The unmanned aerial vehicle can fly at a high speed of more than 60 k...
The paper proposes the development of a set of rules for the resizing of inductive power transfer systems with particular attention to the ones dedicated to the charge of electric vehicles. These rules aim at the construction of down-scaled prototype...
Face recognition is a valuable forensic tool for criminal investigators since it certainly helps in identifying individuals in scenarios of criminal activity like fugitives or child sexual abuse. It is, however, a very challenging task as it must be...
No-reference image quality assessment aims to evaluate image quality based on human subjective perceptions. Current methods face challenges with insufficient ability to focus on global and local information simultaneously and information loss due to...
Background and Objectives: We evaluate deep learning-based segmentation methods for detecting the ulnar nerve in ultrasound (US) images, leveraging the first-ever large US dataset of the ulnar nerve. We compare several widely used segmentation models...
Nowadays, Augmented-Reality (AR) head-mounted displays (HMD) deliver a more immersive visualization of virtual contents, but the available means of interaction, mainly based on gesture and/or voice, are yet limited and obviously lack realism and expr...
Ultrasound imaging is widely employed for breast cancer detection; however, its diagnostic reliability is often constrained by operator dependence and subjective interpretation. Deep learning-based computer-aided diagnosis (CADx) systems offer potent...
This article analyzes an olive oil mill formed of four conical stones used in the milling of the olive. To this end, a study of computer-aided engineering (CAE) was carried out using the parametric software Autodesk Inventor Professional, consisting...
Retrogressive thaw slumps (RTS) are considered one of the most dynamic permafrost disturbance features in the Arctic. Sub-meter resolution multispectral imagery acquired by very high spatial resolution (VHSR) commercial satellite sensors offer unique...
Diffusion-weighted imaging (DWI) combined with radiomics can aid in the differentiation of breast lesions. Segmentation characteristics, however, might influence radiomic features. To evaluate feature stability, we implemented a standardized pipeline...
Recent research on deep learning has been applied to a diversity of fields. In particular, numerous studies have been conducted on self-driving vehicles using end-to-end approaches based on images captured by a single camera. End-to-end controls lear...
Purpose: To develop a preliminary deep learning model that uses diffusion-weighted imaging (DWI) images to classify the severity of neurological impairment caused by ischemic stroke. Materials and Methods: This retrospective study included 851 ischem...
The widespread availability of generative artificial intelligence has increased the volume of images and videos shared online, while making it difficult to verify origin and integrity after routine post-processing such as re-encoding, resizing, and t...
This study focuses on subseasonal 2-m temperature prediction over East Asia for lead times of 1–6 weeks. Based on ERA5 reanalysis data from January 1982 to December 2024, multiple variables, including temperature, wind fields, and geopotential...
Accurate mammographic mass segmentation is crucial for computer-aided breast cancer diagnosis, but remains challenging because masses may be small, low-contrast, irregularly shaped, and partially obscured by dense fibroglandular tissue. Although rece...
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