Among the various fields where deep learning is used, there are challenges to be solved in motion recognition. One is that it is difficult to manage because of the vast amount of data. Another is that it takes a long time to learn due to the complex...
Purpose—Accurate classification of tunnel surrounding rock is essential for safe excavation, timely support adjustment, and risk control during construction. This study proposes an intelligent classification method that links tunnel face image...
Automated food item recognition and recipe recommendation systems have gained increasing importance in dietary management and culinary applications. Recent advancements in Computer Vision, particularly in object detection, classification, and image s...
Communication is integral to every human’s life, allowing individuals to express themselves and understand each other. This process can be challenging for the hearing-impaired population, who rely on sign language for communication due to the l...
A problem was formulated, and methods and algorithms for identifying, recognizing, and classifying micro-objects were developed using problem-oriented image processing systems utilizing the characteristics of image structural components, dynamic mode...
Fruit fly species classification is a fine-grained task as there is a small gap between species. In order to effectively identify and improve the recognition of fruit flies, a fine-grained image-recognition method based on a multi-channel self-attent...
Biomedical information retrieval for diagnosis, treatment and prognosis has been studied for a long time. In particular, image recognition using deep learning has been shown to be very effective for cancers and diseases. In these fields, scaphoid fra...
Wafer maps provide engineers with important information about the root causes of failures during the semiconductor manufacturing process. Through the efficient recognition of the wafer map failure pattern type, the semiconductor manufacturing process...
The study of coastal processes is critical for the protection and development of beach amenities, infrastructure, and properties. Many studies of beach evolution rely on data collected using remote sensing and show that beach evolution can be charact...
Urdu and English are widely used for visual text communications worldwide in public spaces such as signboards and navigation boards. Text in such natural scenes contains useful information for modern-era applications such as language translation for...
The categorization and identification of agricultural imagery constitute the fundamental requisites of contemporary farming practices. Among the various methods employed for image classification and recognition, the convolutional neural network (CNN)...
In this study, we propose a method for training convolutional neural networks to make them identify and classify images with higher classification accuracy. By combining the Cartesian and polar coordinate systems when describing the images, the metho...
In recent years, the development of self-driving cars and their inclusion in our daily life has rapidly transformed from an idea into a reality. One of the main issues that autonomous vehicles must face is the problem of traffic sign detection and re...
Food image classification and recognition is an emerging research area due to its growing importance in the medical and health industries. As India is growing digitally rapidly, an automated Indian food image recognition system will help in the devel...
The critical component of HCI is face recognition technology. Emotional computing heavily relies on the identification of facial emotions. Applications for emotion-driven face animation and dynamic assessment are numerous (FER). Universities have sta...
Traditional indoor human activity recognition (HAR) has been defined as a time-series data classification problem and requires feature extraction. The current indoor HAR systems still lack transparent, interpretable, and explainable approaches that c...
As an important research direction in image and video processing, set-based video recognition requires speed and accuracy. However, the existing static modeling methods focus on computational speed but ignore accuracy, whereas the dynamic modeling me...
Ethnicity recognition has become increasingly important for a wide range of applications, highlighting the need for accurate and robust predictive models. Despite advances in machine learning, ethnicity classification remains a challenging research p...
Background: MR image classification in datasets collected from multiple sources is complicated by inconsistent and missing DICOM metadata. Therefore, we aimed to establish a method for the efficient automatic classification of MR brain sequences. Met...
This review analyzes recent advancements in facial recognition and classification algorithms, emphasizing the critical role of preprocessing techniques in enhancing the algorithms’ accuracy, reliability, and efficiency. Facial image preprocessi...
Crop diseases pose a significant threat to agricultural productivity and global food security. Timely and accurate disease identification is crucial for improving crop yield and quality. While most existing deep learning-based methods focus primarily...
An accurate detection and classification of scenes and objects is essential for interacting with the world, both for living beings and for artificial systems. To reproduce this ability, which is so effective in the animal world, numerous computationa...
The virus responsible for COVID-19 is mutating day by day with more infectious characteristics. With the limited healthcare resources and overburdened medical practitioners, it is almost impossible to contain this virus. The automatic identification...
With the continuous development and progress of science and technology, the increasingly complex electromagnetic environment and the research and development of new radar systems have led to the emergence of various radar signals. Traditional methods...
Deep learning has become the most popular research subject in the fields of artificial intelligence (AI) and machine learning. In October 2013, MIT Technology Review commented that deep learning was a breakthrough technology. Deep learning has made p...
Traditional Collaborative Representation-based Classification algorithms for face recognition (CRC) usually suffer from data uncertainty, especially if it includes various poses and illuminations. To address this issue, in this paper, we design a new...
Weather Report is an initiative from Weathernews Inc. to obtain sky images and current weather conditions from the users of its weather app. This approach can provide supplementary weather information to radar observations and can potentially improve...
Granite residual and slope-wash soils are important disaster-prone geological bodies in the hilly and mountainous areas of Hunan Province, China. Their engineering classification has long relied on manual visual inspection and laboratory testing, whi...
The traffic sign recognition system is a support system that can be useful to give notification and warning to drivers. It may be effective for traffic conditions on the current road traffic system. A robust artificial intelligence based traffic sign...
Sand theft or illegal mining in river dredging areas has been a problem in recent decades. For this reason, increasing the use of artificial intelligence in dredging areas, building automated monitoring systems, and reducing human involvement can eff...
Infrared image recognition technology can work day and night and has a long detection distance. However, the infrared objects have less prior information and external factors in the real-world environment easily interfere with them. Therefore, infrar...
The work contains an original comparison of selected algorithms using artificial neural network models, such as RBF neural networks, and classic algorithms, approaches that are based on structured programming in the image identification task. The exi...
The gear transmission system is the core component in industrial equipment, and its wear state directly affects the reliability and use life of equipment. The wear debris image contains important information on the mechanical wear state. By processin...
In the field of computer vision, large-scale image classification tasks are both important and highly challenging. With the ongoing advances in deep learning and optical character recognition (OCR) technologies, neural networks designed to perform la...
Deep learning (DL) enables the creation of computational models comprising multiple processing layers that learn data representations at multiple levels of abstraction. In the recent past, the use of deep learning has been proliferating, yielding pro...
Thermal cameras, as opposed to RBG cameras, work effectively in extremely low illumination situations and can record data outside of the human visual spectrum. For surveillance and security applications, thermal images have several benefits. However,...
Citrus has become a pivotal industry for the rapid development of agriculture and increasing farmers’ incomes in the main production areas of southern China. Knowing how to diagnose and control citrus huanglongbing has always been a challenge f...
Soybean variety recognition supports germplasm management and intelligent agricultural inspection, but remains challenging because varieties often show subtle inter-class differences, large intra-class imaging variation, and imbalanced samples. This...
Raw image classification datasets generally maintain a long-tailed distribution in the real world. Standard classification algorithms face a substantial issue because many labels only relate to a few categories. The model learning processes will tend...
We present a multi-modal genre recognition framework that considers the modalities audio, text, and image by features extracted from audio signals, album cover images, and lyrics of music tracks. In contrast to pure learning of features by a neural n...
Users of web or chat social networks typically use emojis (e.g., smilies, memes, hearts) to convey in their textual interactions the emotions underlying the context of the communication, aiming for better interpretability, especially for short polyse...
Aphids are small insects that feed on plant sap, and they belong to a superfamily called Aphoidea. They are among the major pests causing damage to citrus crops in most parts of the world. Precise and automatic identification of aphids is needed to u...
This paper introduces a novel approach to handwritten digit recognition based on directional flood simulation and topological feature extraction. While traditional pixel-based methods often struggle with noise, partial occlusion, and limited data, ou...
This paper presents a method for dynamic pattern recognition and classification of one dangerous caterpillar species to allow for its control in maize crops. The use of dynamic pattern recognition supports the identification of patterns in digital im...
Image-based malware classification converts binary software into visual representations, enabling deep visual models to be used for malware family recognition. However, reliable family-level annotation remains labor-intensive and expert-dependent, ma...
Chinese local gazetteer maps contain visual evidence of historical cities and architecture, but their hand-drawn, low-texture, and small-sample characteristics make automatic recognition difficult. This study develops a transfer-learning workflow to...
With the rapid development of intelligent manufacturing and industrial automation, defect recognition and detection of hot-rolled strip steel have become crucial to ensuring both production efficiency and product quality. However, existing hot-rolled...
It is of great practical significance to quickly, accurately, and effectively identify the effects of rice diseases on rice yield. This paper proposes a rice disease identification method based on an improved DenseNet network (DenseNet). This method...
Huanglongbing (HLB) is a highly contagious and devastating citrus disease that causes huge economic losses to the citrus industry. Because it cannot be cured, timely detection of the HLB infection status of plants and removal of diseased trees are ef...
With rapid urbanization, effective waste classification is a critical challenge. Traditional manual methods are time-consuming, labor-intensive, costly, and error-prone, resulting in reduced accuracy. Deep learning has revolutionized this field. Conv...
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