This study analyzes valuable information (image feature information) from pixel-based images to systematize the form generation process utilizing this information. Information in architecture is mainly used as an analytical tool for functional design...
It is crucial for the protection and sustainable development of villages in China to effectively determine the changes that have occurred in traditional villages’ architectural features and the causes of such changes in order to provide timely...
Architecture is a representative of a city. It is also a spatial carrier of urban culture. Identifying the architectural features in a city can help with urban transformation and promote urban development. The use of visual saliency models in regiona...
In embedded software for critical domains such as medical devices and defense, requirement traceability is essential for ensuring quality attributes. Standards and regulations mandate traceability between requirements and artifacts such as design ele...
Video-based person re-identification is an important task with the challenges of lighting variation, low-resolution images, background clutter, occlusion, and human appearance similarity in the multi-camera visual sensor networks. In this paper, we p...
The article covers the results of the study of a historical wooden holiday architectural ensemble called Świdermajer, located on the outskirts of Warsaw in Poland. The fashion for traveling and resting within natural surroundings emerged in the...
Speech lie detection is a technique that analyzes speech signals in detail to determine whether a speaker is lying. It has significant application value and has attracted attention from various fields. However, existing speech lie detection algorithm...
Hybrid spam is an undesirable e-mail (electronic mail) that contains both image and text parts. It is more harmful and complex as compared to image-based and text-based spam e-mail. Thus, an efficient and intelligent approach is required to distingui...
Estimating the state of health of lithium-ion batteries in energy storage systems is a key step in their subsequent safety monitoring and energy optimization management. This study proposes a method for estimating the state of health of lithium-ion b...
One of the major challenges in cancer therapy lies in the limited targeting specificity exhibited by existing anti-cancer drugs. Tumor-homing peptides (THPs) have emerged as a promising solution to this issue, due to their capability to specifically...
Geographical and environmental conditions were two of the most important factors on the design and construction of traditional architecture. Traditional earthen architecture is found throughout the Iberian Peninsula in numerous constructive technique...
Traditional vernacular architecture is an important component of historical and cultural heritage, and the accurate identification of its construction period is of great significance for architectural heritage conservation, historical research, and u...
Micro-expressions, which are spontaneous and difficult to suppress, reveal a person’s true emotions. They are characterized by short duration and low intensity, making the task of micro-expression recognition challenging in the field of emotion...
Tulou, Tubao, and Zhailu all belong to the same vernacular architectural defensive rammed earth dwellings in Fujian; however, because of the similarity of their earthen defensive functions and fortress architectural systems, they are easily confused...
An autonomous concrete crack inspection system is necessary for preventing hazardous incidents arising from deteriorated concrete surfaces. In this paper, we present a concrete crack detection framework to aid the process of automated inspection. The...
This paper proposes a real-time feature extraction VLSI architecture for high-resolution images based on the accelerated KAZE algorithm. Firstly, a new system architecture is proposed. It increases the system throughput, provides flexibility in imag...
Automatic speech emotion recognition is a challenging task due to the gap between acoustic features and human emotions, which rely strongly on the discriminative acoustic features extracted for a given recognition task. We propose a novel deep neural...
In this paper, we present a novel pipelined near real-time speaker recognition architecture that enhances the performance of speaker recognition by exploiting the advantages of hybrid feature extraction techniques that contain the features of Gabor F...
Although some researchers have proposed the Field Programmable Gate Array (FPGA) architectures of Feature From Accelerated Segment Test (FAST) and Binary Robust Independent Elementary Features (BRIEF) algorithm, there is no consideration of image dat...
Advances in deep learning and computer vision techniques have made impacts in the field of remote sensing, enabling efficient data analysis for applications such as land cover classification and change detection. Convolutional neural networks (CNNs)...
The spread of biometric systems utilizing fingerprints has increased the need for advanced spoof detection techniques, but training convolutional neural networks (CNNs) with the limited number of images available in fingerprint datasets poses signifi...
A multi-agent architecture for a Non-Intrusive Load Monitoring (NILM) solution is presented and evaluated. The underlying rationale for such an architecture is that each agent (load event detection, feature extraction, and classification) outperforms...
Addressing the inefficiency, subjective errors, and limited adaptability of existing methods for surveying complex ancient structures, this study presents an intelligent hierarchical algorithm for generating line drawings guided by structured archite...
In recent years, researchers have proposed many deep learning algorithms for data representation learning. However, most deep networks require extensive training data and a lot of training time to obtain good results. In this paper, we propose a nove...
In the realm of architectural computing, this study explores the integration of parametric design with machine learning algorithms to advance the early design phase of tall buildings with outer diagrid systems. The success of such an endeavor relies...
In the domain of automatic visual inspection for miniature capacitor quality control, the task of accurately detecting defects presents a formidable challenge. This challenge stems primarily from the small size and limited sample availability of defe...
The study highlights the morphological features of mud-brick architecture in Syria, based on a descriptive and analytical approach. The research begins with a theoretical introduction about the studied area and mud-brick architecture, then their urba...
Recent advances in deep learning have witnessed the wide application of convolutional neural networks (CNNs), Transformer models, and Mamba models in optical remote sensing image (ORSI) analysis, particularly for salient object detection (SOD) tasks...
Given the widespread influence of U-Net and FPN network architectures on infrared small target detection tasks on existing models, these structures frequently incorporate a significant number of downsampling operations, thereby rendering the preserva...
In the current landscape dominated by Artificial Intelligence, the integration of Machine Learning and Deep Learning within the realm of Cultural Heritage, particularly within architectural contexts, is paramount for the efficient processing and inte...
The increasing size of recent deep neural networks, particularly when applied to learning across multiple domains, limits their deployment in resource-constrained environments. To address this issue, this study proposes a lightweight neural architect...
The Guangdong historical trail comprises two ancient trails, known as Yile (宜乐) and Xijing (西京); can be found within the borders of Lechang (乐昌); and is an integral part of the northern section of the Guangdo...
This paper proposes a tracking method combining feature enhancement and template update, aiming to solve the problems of existing trackers lacking global information attention, weak feature characterization ability, and not being well adapted to the...
Diabetic retinopathy is the leading cause of blindness suffered by working-age adults. The increase in the population diagnosed with DR can be prevented by screening and early treatment of eye damage. This screening process can be conducted by utiliz...
The optimization capabilities of Kolmogorov–Arnold Networks (KANs) remain largely unexplored, which has limited their practical use in video anomaly recognition compared to conventional 3D-CNNs. To address this gap, we introduce a novel hybrid...
Traditional villages, protected as cultural heritage in our country, are rich in historical information, cultural landscapes, and traditional domestic architecture. This article explores the spatial distribution of traditional villages and proposes a...
This study aims to address a series of challenges in infrared small target detection, particularly in complex backgrounds and high-noise environments. In response to these issues, we propose a deep learning model called the Feature Multi-Scale Enhanc...
The investigation, evaluation, and dynamic monitoring of traditional village buildings are crucial for the protection and inheritance of their architectural styles. This study takes traditional villages in Shandong Province, China, as an example, emp...
This systematic review focused on the effect of the educational environment design on students’ and teachers’ performance, satisfaction, and wellbeing. Starting from a bulk of 1307 articles, a set of N = 68 empirical papers was selected a...
1 April 2024
Background: This research goes into in deep learning technologies within the realm of medical imaging, with a specific focus on the detection of anomalies in medical pathology, emphasizing breast cancer. It underscores the critical importance of segm...
Recent advancements in face super resolution (FSR) have been propelled by deep learning techniques using convolutional neural networks (CNN). However, existing methods still struggle with effectively capturing global facial structure information, lea...
The identification of ships in Synthetic Aperture Radar (SAR) imagery is critical for effective maritime surveillance. The advent of deep learning has significantly improved the accuracy of SAR ship classification and recognition. However, distinguis...
Blurring is one of the main degradation factors in image degradation, so image deblurring is of great interest as a fundamental problem in low-level computer vision. Because of the limited receptive field, traditional CNNs lack global fuzzy region mo...
Breast cancer remains one of the most prevalent and deadly cancers affecting women worldwide. Early detection is crucial, particularly for younger women, as traditional screening methods like mammography often struggle with accuracy in cases of dense...
AYOLO introduces a novel fusion architecture that integrates unsupervised learning techniques with Vision Transformers, leveraging the YOLO series models as its foundation. This innovation enables the effective utilization of rich, unlabeled data, es...
Simple Baseline has become a dominant benchmark in human pose estimation (HPE) due to its excellent performance and simple design. However, its “strong encoder + simple decoder” architectural paradigm suffers from two core limitations: (1...
In complex electromagnetic environments, radar systems face increasing challenges from advanced jamming techniques. These challenges mainly stem from the diversity of jamming patterns, the complexity of compound jamming signals, and the difficulty of...
Remote photoplethysmography (rPPG) refers to a non-contact technique that measures heart rate through analyzing the subtle signal changes of facial blood flow captured by video sensors. It is widely used in contactless medical monitoring, remote heal...
Attention mechanisms can improve the performance of neural networks, but the recent attention networks bring a greater computational overhead while improving network performance. How to maintain model performance while reducing complexity is a hot re...
To address the challenges brought by the high penetration of renewable energy in power systems, such as multi-scale dynamic interactions, high feature dimensionality, and limited model generalization, this paper proposes a transient stability assessm...
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