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Topic Review
Breast Density and Pre-Trained Convolutional Neural Network
Breast density describes the amount of fibrous and glandular tissue in a breast compared with the amount of fatty tissue. The breast density is assigned to one of four classes in the mammogram report based on the ACR BI-RADS standard. Convolutional Neural Network (CNN) are a type of artificial neural network usually used for classification and computer vision tasks. Therefore, CNNs are considered efficient tools for medical imaging classification.
  • 1.0K
  • 21 Jun 2022
Topic Review
Simulate Gene Expression and Infer Gene Regulatory Networks
The ability to simulate gene expression and infer gene regulatory networks has vast potential applications in various fields, including medicine, agriculture, and environmental science. Machine learning approaches to simulate gene expression and infer gene regulatory networks have gained significant attention as a promising area of research.
  • 1.0K
  • 30 Aug 2023
Topic Review
Coronavirus
Coronaviruses are indeed a huge family of viruses that are found both in humans and animals. Seven different types have been identified, including the ones that caused COVID-19 and the SARS and MERS illnesses.
  • 1.0K
  • 09 Nov 2022
Topic Review
Strategy for Catastrophic Forgetting Reduction in Incremental Learning
Catastrophic forgetting or catastrophic interference is a serious problem in continuous learning in machine learning. It happens not only in traditional machine learning algorithms such as SVM (Support Vector Machine), NB (Naive Bayes), DT (Decision Tree), and CRF (Conditional Random Field) but also in DNNs.
  • 1.0K
  • 05 Jun 2023
Topic Review
Troubleshooting Chatbots Applied to ATM Technical Maintenance Support
The banking industry has been employing artificial intelligence (AI) technologies to enhance the quality of its services. AI algorithms, such as natural language understanding (NLU), have been integrated into chatbots to improve banking applications. 
  • 1.0K
  • 21 Jun 2023
Topic Review
Surface Defect Detection of Strip-Steel
Surface-defect detection is crucial for assuring the quality of strip-steel manufacturing. Strip-steel surface-defect detection requires defect classification and precision localization, which is a challenge in real-world applications.
  • 1.0K
  • 14 Sep 2022
Topic Review
Neural Architecture Search: A Computer Vision Perspective
Deep learning (DL) has been widely studied using various methods across the globe, especially with respect to training methods and network structures, proving highly effective in a wide range of tasks and applications, including image, speech, and text recognition. One important aspect of this advancement is involved in the effort of designing and upgrading neural architectures, which has been consistently attempted thus far. However, designing such architectures requires the combined knowledge and know-how of experts from each relevant discipline and a series of trial-and-error steps. In this light, automated neural architecture search (NAS) methods are increasingly at the center of attention.
  • 1.0K
  • 06 May 2023
Topic Review
Sustainability, Digital Technologies and the Circular Economy
The textile and clothing (T&C) industry is not usually viewed as an exemplar of sustainable development and the circular economy (CE), as the industry has hitherto developed its products in a linear fashion, with relatively little recycling of the finished goods. 
  • 1.0K
  • 03 Jul 2023
Topic Review
Vision-Based Gait Recognition
Identifying people’s identity by using behavioral biometrics has attracted many researchers’ attention in the biometrics industry. Gait is a behavioral trait, whereby an individual is identified based on their walking style. Over the years, gait recognition has been performed by using handcrafted approaches. Due to several covariates’ effects, the competence of the approach has been compromised. Deep learning is an emerging algorithm in the biometrics field, which has the capability to tackle the covariates and produce highly accurate results. 
  • 1.0K
  • 12 Aug 2022
Topic Review
Artificial Intelligence-Based Cyber Security in Industry 4.0
The increase in cyber-attacks impacts the performance of organizations in the industrial sector, exploiting the vulnerabilities of networked machines. The increasing digitization and technologies present in the context of Industry 4.0 have led to a rise in investments in innovation and automation. However, there are risks associated with this digital transformation, particularly regarding cyber security. Targeted cyber-attacks are constantly changing and improving their attack strategies, with a focus on applying artificial intelligence in the execution process. Artificial Intelligence-based cyber-attacks can be used in conjunction with conventional technologies, generating exponential damage in organizations in Industry 4.0. The increasing reliance on networked information technology has increased the cyber-attack surface. 
  • 1.0K
  • 20 Nov 2023
Topic Review
Reinforcement Learning, Knowledge Distillation, and Channel Pruning
The methods used for model compression and acceleration are primarily divided into five categories—network pruning, parameter quantization, low-rank decomposition, lightweight network design, and knowledge distillation—such that the scope of actions and design ideas for each method are different.
  • 1.0K
  • 12 Dec 2023
Topic Review
3D Object Detection with Differential Point Clouds
3D object detection based on point clouds has many applications in natural scenes, especially in autonomous driving. Point cloud data provide reliable geometric and depth information. 
  • 1.0K
  • 24 Dec 2022
Topic Review
NER&RE Techniques on Clinical Texts
Out of the various text mining tasks and techniques, our goal in this paper is to review the current state-of-the-art in Clinical Named Entity Recognition (NER) and Relationship Extraction (RE)-based techniques. Clinical NER is a natural language processing (NLP) method used for extracting important medical concepts and events i.e., clinical NEs from the data. Relationship Extraction (RE) is used for detecting and classifying the annotated semantic relationships between the recognized entities.
  • 1.0K
  • 30 Sep 2021
Topic Review
Surrogate-Based Optimisation
Surrogate-based optimisation (SBO) algorithms are a powerful technique that combine machine learning and optimisation to solve expensive optimisation problems. This type of problem appears when dealing with computationally expensive simulators or algorithms. By approximating the expensive part of the optimisation problem with a surrogate, the number of expensive function evaluations can be reduced.
  • 1.0K
  • 31 Mar 2022
Topic Review
Dynamic Fault Tree analysis method
The Entry briefly introduces the Dynamic Fault Tree analysis method proposed by P. Gao et al on the 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC).
  • 1.0K
  • 04 Apr 2022
Topic Review
Approach for Overlapped Segmentation of Bacterial Cell Images
Scanning electron microscopy (SEM) techniques have been extensively performed to image and study bacterial cells with high-resolution images. Bacterial image segmentation in SEM images is an essential task to distinguish an object of interest and its specific region.
  • 1.0K
  • 15 Dec 2022
Topic Review
Corpus Statistics Empowered Document Classification
In natural language processing (NLP), document classification is an important task that relies on the proper thematic representation of the documents. Gaussian mixture-based clustering is widespread for capturing rich thematic semantics but ignores emphasizing potential terms in the corpus. Moreover, the soft clustering approach causes long-tail noise by putting every word into every cluster, which affects the natural thematic representation of documents and their proper classification. It is more challenging to capture semantic insights when dealing with short-length documents where word co-occurrence information is limited.
  • 1.0K
  • 05 Aug 2022
Topic Review
Deep Neural Networks
The fundamental principles and structures of deep learning (DL) are examined herein. The specific roles and functions of the diverse layers that make up deep networks are discussed, and the importance of evaluation metrics, which serve as crucial tools for gauging the effectiveness of these models, are emphasized. Commonly used architectures in medical image segmentation are also introduced.
  • 1.0K
  • 29 Nov 2023
Topic Review
Deep Learning Methods for Solving the NLI Problem
Natural language inference (NLI) is one of the most important natural language understanding (NLU) tasks. NLI expresses the ability to infer information during spoken or written communication. The NLI task concerns the determination of the entailment relation of a pair of sentences, called the premise and hypothesis. If the premise entails the hypothesis, the pair is labeled as an “entailment”. If the hypothesis contradicts the premise, the pair is labeled a “contradiction”, and if there is not enough information to infer a relationship, the pair is labeled as “neutral”.
  • 1.0K
  • 26 Apr 2024
Topic Review
Brain Tumor Segmentation
Segmentation of brain tumor images from magnetic resonance imaging (MRI) is a challenging topic in medical image analysis. The brain tumor can take many shapes, and MRI images vary considerably in intensity, making lesion detection difficult for radiologists. Image segmentation is the action of grouping pixels according to predefined criteria, in order to build regions or classes of pixels. There are several methods of image segmentation: methods based on contours, regions, classification, or hybrid. Segmentation and its automation remain today one of the major challenges in MRI, mainly in relation to brain tumor images, in order to help the practitioner in his daily practice, in the presence of a huge volume of images. 
  • 1.0K
  • 26 Sep 2022
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