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Topic Review
Convolutional Neural Network-Based Layer-Adaptive Ground Control Points Extraction
Ground Control Points (GCPs) are of great significance for applications involving the registration and fusion of heterologous remote sensing images (RSIs). However, utilizing low-level information rather than deep features, traditional methods based on intensity and local image features turn out to be unsuitable for heterologous RSIs because of the large nonlinear radiation difference (NRD), inconsistent resolutions, and geometric distortions. Additionally, the limitations of current heterologous datasets and existing deep-learning-based methods make it difficult to obtain enough precision GCPs from different kinds of heterologous RSIs, especially for thermal infrared (TIR) images that present low spatial resolution and poor contrast.
  • 422
  • 02 Jun 2023
Topic Review
Underwater Sensor Networks
The issue of limited energy resources is crucial for underwater wireless sensor networks (UWSNs) because these networks operate in remote and harsh environments where access to power sources is limited. Overcoming the energy constraints is necessary to ensure the long-term functionality and sustainability of UWSN, enabling continuous data collection and communication for various applications such as environmental monitoring and surveillance.
  • 422
  • 21 Aug 2023
Topic Review
Classification of Tumor in Brain Magnetic Resonance Images
Brain tumors can cause serious health complications and lead to death if not detected accurately. Therefore, early-stage detection of brain tumors and accurate classification of types of brain tumors play a major role in diagnosis. Timely detection, diagnosis, and classification of brain tumors have been instrumental in effective treatment planning for the recovery and life extension of the patient. Brain tumor detection is a procedure to differentiate the abnormal tissues for example active tumor tissue, edema tissue from normal tissues for example gray matter, white matter.
  • 422
  • 02 Apr 2024
Topic Review
UAV-Based Computer Vision for Tree Inventory
Accurate and efficient orchard tree inventories are essential for acquiring up-to-date information, which is necessary for effective treatments and crop insurance purposes. Surveying orchard trees, including tasks such as counting, locating, and assessing health status, plays a vital role in predicting production volumes and facilitating orchard management.
  • 421
  • 23 Aug 2023
Topic Review
Controlling Upper Limb Prostheses Using Sonomyography
A ground-breaking study by Zheng et al. investigated whether ultrasound imaging of the forearm might be used to control a powered prosthesis, and the term “sonomyography” (SMG) was coined by the group. Ultrasound signals have recently garnered the interest of researchers in the area of HMIs because they can collect information from both superficial and deep muscles and so provide more comprehensive information than other techniques. Due to the great spatiotemporal resolution and specificity of ultrasound measurements of muscle deformation, researchers have been able to infer fine volitional motor activities, such as finger motions and the dexterous control of robotic hands.
  • 420
  • 27 Feb 2023
Topic Review
Advancements in Glaucoma Diagnosis
The progress of artificial intelligence algorithms in digital image processing and automatic diagnosis studies of the eye disease glaucoma has been growing and presenting essential advances to guarantee better clinical care for the population.
  • 420
  • 14 Mar 2024
Topic Review
FCAN–XGBoost
Emotion recognition has broad application prospects in fields such as artificial intelligence (AI), intelligent healthcare, remote education, and virtual reality (VR) games. Accurately recognizing human emotions is one of the most urgent issues in the brain–computer interface. FCAN XGBoost is a electroencephalogram (EEG) based emotion recognition model that can quickly and accurately recognize four types of emotions in EEG.
  • 420
  • 05 Sep 2023
Topic Review
Solar Energy Generation Prediction
Energy, or more specifically electricity, is one of the most significant pillars of society. Solar Photovoltaic energy has emerged as the most flourishing source of power generation. Not only is it a clean and renewable energy, but it is also economically accessible with minimal maintenance. Nevertheless, they have the disadvantage of high dependence on climatic factors, significant variability and high cost of energy storage. Hence, forecasting the generation of Photovoltaic (PV) installations for a given period of time can help to make optimal use of resources, allowing for reduced emissions, lower costs, safe operation and better integration into the grid.
  • 419
  • 30 Nov 2023
Topic Review
Computer-Aided Diagnosis Approach for Breast Cancer
Breast cancer is a gigantic burden on humanity, causing the loss of enormous numbers of lives and amounts of money. It is the world’s leading type of cancer among women and a leading cause of mortality and morbidity. The histopathological examination of breast tissue biopsies is the gold standard for diagnosis. A computer-aided diagnosis (CAD) system based on deep learning is developed to ease the pathologist’s mission A new transfer learning approach is introduced for breast cancer classification using a set of pre-trained Convolutional Neural Network (CNN) models with the help of data augmentation techniques. Multiple experiments are performed to analyze the performance of these pre-trained CNN models through carrying out magnification dependent and magnification independent binary and eight-class classifications. Xception model has shown a promising performance through achieving the highest classification accuracy for all experiments.
  • 418
  • 17 Oct 2022
Topic Review
Cardiac Failure Forecasting
Accurate prediction of heart failure can help prevent life-threatening situations. Several factors contribute to the risk of heart failure, including underlying heart diseases such as coronary artery disease or heart attack, diabetes, hypertension, obesity, certain medications, and lifestyle habits such as smoking and excessive alcohol intake. Machine learning approaches to predict and detect heart disease hold significant potential for clinical utility but face several challenges in their development and implementation.
  • 418
  • 15 Aug 2023
Topic Review
Neuromorphic Sentiment Analysis Using Spiking Neural Networks
Spiking neural networks, often employed to bridge the gap between machine learning and neuroscience fields, are considered a promising solution for resource-constrained applications. Since deploying spiking neural networks on traditional von-Newman architectures requires significant processing time and high power, typically, neuromorphic hardware is created to execute spiking neural networks. The objective of neuromorphic devices is to mimic the distinctive functionalities of the human brain in terms of energy efficiency, computational power, and robust learning. 
  • 418
  • 20 Sep 2023
Topic Review
Point Cloud Object Classifications
A point cloud is a set of individual data points in a three-dimensional (3D) space. Proper collection of these data points may create an identifiable 3D structure, map, or model.
  • 417
  • 12 May 2023
Topic Review
Impacts of Surface Microchannels on Porous Fibrous Media
The microchannel increases the permeability of flow both in the directions parallel and vertical to the microchannel direction. The microchannel plays as the highway for the pass of reactants while the rest of the smaller pore size provides higher resistance for better catalyst support, and the propagation path in the network with microchannels is more even and predictable. 
  • 416
  • 21 Dec 2021
Topic Review
Anti-Aliasing Attention U-net Model for Skin Lesion Segmentation
The need for a lightweight and reliable segmentation algorithm is critical in various biomedical image-prediction applications. However, the limited quantity of data presents a significant challenge for image segmentation. Additionally, low image quality negatively impacts the efficiency of segmentation, and previous deep learning models for image segmentation require large parameters with hundreds of millions of computations, resulting in high costs and processing times.
  • 416
  • 31 Jul 2023
Topic Review
Artificial Intelligence Techniques in Concrete
Due to the speed of artificial intelligence (AI) techniques in solving engineering problems, there has been a tendency to use these techniques in various fields of civil engineering, including designing construction materials (concrete mixtures for example) or estimating their properties.  As it is hard to predict the compressive strength of concrete due to the different nonlinearities inherent in the mixture designs, various concrete companies are continuously looking to use new methods and technologies to predict the compressive strength. Such methods include numerical modelling and artificial intelligence due to their advantages. 
  • 414
  • 07 Oct 2023
Topic Review
Compensation of Pressure Sensor Drifts
Pressure sensor chips embodied in very tiny packages are deployed in a wide range of advanced applications. Examples of them range from industrial to altitude location services. They are also becoming increasingly pervasive in many other fields, ranging from industrial to military to consumer. However, these sensors, which are very cheap to manufacture in silicon, are strongly affected by thermal, mechanical and environmental stresses, which ultimately affect their measurement accuracy in the form of variations in gain, hysteresis, and nonlinear responses. To compensate induced drift in measurements, several neural networks were devised and be applied to stresses caused by two thermal cycles: 260 C for 10-40 seconds (JEDEC soldering procedure) and 100 C for two hours. These models were characterized in accuracy and deployability on tiny embedded devices and improved accuracy was observed.
  • 414
  • 08 Dec 2023
Topic Review
Epileptic Disorder Detection of Seizures Using Encephalography Signals
Epilepsy is a nervous system disorder. Encephalography (EEG) is a generally utilized clinical approach for recording electrical activity in the brain. Although there are a number of datasets available, most of them are imbalanced due to the presence of fewer epileptic EEG signals compared with non-epileptic EEG signals.
  • 413
  • 23 Sep 2022
Topic Review
Graph Neural Networks for Parkinson’s Disease
Graph neural networks (GNNs) have been increasingly employed in the field of Parkinson’s disease (PD) research. The use of GNNs provides a promising approach to address the complex relationship between various clinical and non-clinical factors that contribute to the progression of PD. 
  • 413
  • 13 Nov 2023
Topic Review
Arabic Text Clustering
Arabic text clustering is an essential topic in Arabic Natural Language Processing (ANLP). Its significance resides in various applications, such as document indexing, categorization, user review analysis, and others. 
  • 412
  • 20 Nov 2023
Topic Review
Processing and Analysis of Label-Free Images
Time-lapse microscopy imaging is a key approach for an increasing number of biological and biomedical studies to observe the dynamic behavior of cells over time which helps quantify important data, such as the number of cells and their sizes, shapes, and dynamic interactions across time. Label-free imaging is an essential strategy for such studies as it ensures that native cell behavior remains uninfluenced by the recording process.
  • 411
  • 11 Oct 2022
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