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Topic Review
Resilience in the Cyberworld
Resilience is a feature that is gaining more and more attention in computer science and computer engineering. However, the definition of resilience for the cyber landscape, especially embedded systems, is not yet clear. 
  • 1.1K
  • 25 Nov 2021
Topic Review
Deep Learning Models for Radiography in Chest Disease
Chest X-ray radiography (CXR) is among the most frequently used medical imaging modalities. It has a preeminent value in the detection of multiple life-threatening diseases. Radiologists can visually inspect CXR images for the presence of diseases. Most thoracic diseases have very similar patterns, which makes diagnosis prone to human error and leads to misdiagnosis. Machine learning (ML) and deep learning (DL) provided techniques to make this task more efficient and faster. Numerous experiments in the diagnosis of various diseases proved the potential of these techniques.
  • 1.1K
  • 18 Jan 2023
Topic Review
Remote Sensing Applications in Almond Orchards
Almond cultivation is of great socio-economic importance worldwide. With the demand for almonds steadily increasing due to their nutritional value and versatility, optimizing the management of almond orchards becomes crucial to promote sustainable agriculture and ensure food security.
  • 1.1K
  • 29 Feb 2024
Topic Review
Train Multiplayer First-Person Shooter Game Agents
Artificial Intelligence bots are extensively used in multiplayer First-Person Shooter (FPS) games. By using Machine Learning techniques, we can improve their performance and bring them to human skill levels.
  • 1.1K
  • 18 Mar 2024
Topic Review
Colon Cancer Diagnosis
Researchers presents a comprehensive survey on the diagnosis of colon cancer. This covers many aspects related to colon cancer, such as its symptoms and grades as well as the available imaging modalities (particularly, histopathology images used for analysis) in addition to common diagnosis systems. Furthermore, the most widely used datasets and performance evaluation metrics are discussed. Researchers provide a comprehensive review of the current studies on colon cancer, classified into deep-learning (DL) and machine-learning (ML) techniques, and researchers identify their main strengths and limitations. These techniques provide extensive support for identifying the early stages of cancer that lead to early treatment of the disease and produce a lower mortality rate compared with the rate produced after symptoms develop. In addition, these methods can help to prevent colorectal cancer from progressing through the removal of pre-malignant polyps, which can be achieved using screening tests to make the disease easier to diagnose. Finally, the existing challenges and future research directions that open the way for future work in this field are presented.
  • 1.1K
  • 07 Dec 2022
Topic Review
Forensic Methods for Image Inpainting
The rapid development of digital image inpainting technology is causing serious hidden danger to the security of multimedia information. Efforts have been devoted to developing forensic methods for image inpainting. They can be roughly divided into the following two categories: conventional inpainting forensics methods and deep learning-based inpainting forensics methods.
  • 1.1K
  • 26 Jun 2023
Topic Review
Credit Card Fraud Detection
With the rapid developments in electronic commerce and digital payment technologies, credit card transactions have increased significantly. Machine learning (ML) has been vital in analyzing customer data to detect and prevent fraud.
  • 1.1K
  • 29 Jun 2023
Topic Review
Accurate Measurement of Urban Environments
In the field of urban environment analysis research, image segmentation technology that groups important objects in the urban landscape image in pixel units has been the subject of increased attention.
  • 1.1K
  • 10 Nov 2023
Topic Review
Gastrointestinal Disease Classification
Gastrointestinal (GI) tract diseases are on the rise in the world. These diseases can have fatal consequences if not diagnosed in the initial stages. WCE (wireless capsule endoscopy) is the advanced technology used to inspect gastrointestinal diseases such as ulcerative-colitis, polyps, esophagitis, and ulcers. WCE produces thousands of frames for a single patient’s procedure for which manual examination is tiresome, time-consuming, and prone to error; therefore, an automated procedure is needed.
  • 1.1K
  • 26 Jan 2024
Topic Review
Hybrid Digital Food Twin
Food production is highly complex due to the various chemo-physical and biological processes that must be controlled to transform ingredients into final products. Further, production processes must be adapted to the variability of the ingredients, e.g., due to seasonal fluctuations of raw material quality. Digital twins are known from Industry 4.0 as a method to model, simulate, and optimize processes. Such a digital food twin has to consider the changes within the food due to micro-biological, chemical, and physical processes. Consequently, researchers propose the concept of a hybrid digital twin, which integrates simulation and data science (i.e., machine learning) to combine a data-driven perspective, simulations, and scientific models to describe the food product and the food processing process. 
  • 1.1K
  • 16 Sep 2022
Topic Review
Impact of AI on the Future of Work
Artificial Intelligence (AI) is transforming the way we work, creating new opportunities for efficiency, innovation, and growth. However, it also poses several challenges, including job displacement, skills gaps, and ethical concerns. This research explores the potential impact of AI on the future of work and discusses strategies for addressing these challenges. By embracing AI technology and investing in the development of new skills, we can create a future of work that is more productive, equitable, and sustainable.
  • 1.1K
  • 22 May 2023
Topic Review
Hand Pose Recognition Using Parallel Multi Stream CNN
Recently, several computer applications provided operating mode through pointing fingers, waving hands, and with body movement instead of a mouse, keyboard, audio, or touch input such as sign language recognition, robot control, games, appliances control, and smart surveillance. With the increase of hand-pose-based applications, new challenges in this domain have also emerged. Support vector machines and neural networks have been extensively used in this domain using conventional RGB data, which are not very effective for adequate performance.
  • 1.1K
  • 12 Jan 2022
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.
  • 1.1K
  • 14 Sep 2022
Topic Review
MoRAL-AI: AI-based Liver Transplantation Model
Novel model to predict HCC recurrence after liver transplantation based on deep learning
  • 1.1K
  • 29 Jan 2021
Topic Review
Deep Learning Approaches for Detecting Fake News
The unregulated proliferation of counterfeit news creation and dissemination poses a constant threat to democracy. Fake news articles have the power to persuade individuals, leaving them perplexed. State of the art in deep learning techniques for fake news detection are described herein.
  • 1.1K
  • 10 Mar 2023
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.
  • 1.1K
  • 21 Jun 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. 
  • 1.1K
  • 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.
  • 1.1K
  • 12 Dec 2023
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. 
  • 1.1K
  • 26 Sep 2022
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”.
  • 1.1K
  • 26 Apr 2024
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