Improve Fine-Grained Feature Learning in Fine-Grained DataSet GAI by Hai Peng Wang, Zhi Qing Geng

“…This approach of sacrificing some features to enhance retained features elucidates the essence of neural networks from a new perspective.…”
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Freeway Traffic Speed Prediction under the Intelligent Driving Environment: A Deep Learning Approach by Chengying Hua, Wei (David) Fan

“…To improve the prediction performance and investigate the temporal features, this study focuses on emerging deep neural networks (DNNs) using the Caltrans Performance Measurement System (PeMS) data. …”
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Deep Learning-Enabled Automatic Detection of Bridges for Promoting Transportation Surveillance under Different Imaging Conditions by Peng Han, Xiaoxia Yang

“…It is obvious that the generalization abilities of these deep neural networks are significantly improved using this data augmentation strategy. …”
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Autonomous Robotic Manipulation: Real-Time, Deep-Learning Approach for Grasping of Unknown Objects by Malak H. Sayour, Sharbel E. Kozhaya, Samer S. Saab

“…This paper presents a full grasping pipeline proposing a real-time data-driven deep-learning approach for robotic grasping of unknown objects using MATLAB and convolutional neural networks. The proposed approach employs RGB-D image data acquired from an eye-in-hand camera centering the object of interest in the field of view using visual servoing. …”
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An Improved Direct Torque Control with an Advanced Broken-Bar Fault Diagnosis for Induction Motor Drives by Oualid Aissa, Abderrahim Reffas, Hicham Talhaoui, Djamel Ziane, Abdelhakim Saim

“…This paper presents an advanced strategy combining fuzzy logic and artificial neural networks (ANNs) for direct torque control (DTC) and broken-bar fault diagnosis in induction motors. …”
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A Virtual Fabrication and High-Performance Design of 65 nm Nanocrystal Floating-Gate Transistor by Thinh Dang Cong, Trang Hoang

“…Floating-gate transistor lies at the heart of many aspects of semiconductor applications such as neural networks, analog mixed-signal, neuromorphic computing, and especially in nonvolatile memories. …”
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Deep Learning algorithm for the assessment of the first damage initiation monitoring the energy release of materials by Dario Santonocito, Dario Milone

“…This work aims to create a universal methodology that predicts the limit stress by assessing the change in temperature trend by adopting Neural Networks. A Deep Learning algorithm has been created and trained on experimental data coming from static tensile tests performed on several classes of materials (steels, plastics, composite materials). …”
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An Explainable Stacked Ensemble Model for Static Route-Free Estimation of Time of Arrival by Sören Schleibaum, Jörg P. Müller, Monika Sester

“…However, these models are mostly black box neural networks. Hence, the resulting predictions are difficult to explain to users. …”
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Machine Learning Approaches for Developing Land Cover Mapping by Ali Alzahrani, Awos Kanan

“…In this work, a genetic algorithm-based feature selection approach is used to enhance the performance of urban land cover classification. Neural networks (NNs) and random forest (RF) classifiers were used to evaluate the proposed approach on a recent urban land cover dataset of nine different classes. …”
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The Application of Differing Machine Learning Algorithms and Their Related Performance in Detecting Skin Cancers and Melanomas by Suboh Alkhushayni, Du’a Al-zaleq, Luwis Andradi, Patrick Flynn

“…We tested combinations of models, including convolutional neural networks (CNNs), and various layers of data manipulation, such as the application of Gaussian functions and trimming of images to improve accuracy. …”
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Visual Impairment Spatial Awareness System for Indoor Navigation and Daily Activities by Xinrui Yu, Jafar Saniie

“…At the foundational level, the system employs augmented reality (AR) markers for indoor positioning, neural networks for advanced object detection and tracking, and depth information for precise object localization. …”
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Effectiveness of the Spatial Domain Techniques in Digital Image Steganography by Rosshini Selvamani, Yusliza Yusoff

“…In addition to using statistics as a foundation, convolution neural networks (CNN), generative adversarial networks (GAN), coverless approaches, and machine learning are all used to construct steganographic methods. …”
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Advancements of Deep Learning Model-Based Rehabilitation Training System by Xu Chiyu

“…In this paper, one of the studies proposed the concept of posture-guided matching based on paired Siamese Convolutional Neural Networks (SCNN), abbreviated as ST-AMCNN, on a dataset of the traditional Chinese rehabilitation training Baduanjin. …”
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Graphic Perception System for Visually Impaired Groups by Jingzi Wen

“…In recent years, deep neural networks have promoted the development of image object recognition. …”
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Advanced Breast Cancer Diagnostics With PolyBreastVit: A Combined PolyNet and Vision Transformer Approach by Visalakshi Annepu, Mohamed Abbas, Hanumatha Rao Bitra, Naveen Kumar Vaegae, Kalapraveen Bagadi

“…This paper presents the latest development of breast cancer diagnostic tools through medical imaging incorporating convolutional neural networks (CNNs) and transformer models for radiologists.…”
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Inferring causal connectivity from pairwise recordings and optogenetics. by Mikkel Elle Lepperød, Tristan Stöber, Torkel Hafting, Marianne Fyhn, Konrad Paul Kording

“…Combined, these methods can estimate (causal) effective connectivity by exploiting the weak, approximately random signal resulting from the interaction between stimulation and the absolute refractory period of the neuron. In simulated neural networks, we find that estimates using ideas from IV and DiD outperform naïve techniques suggesting that methods from causal inference can be useful to disentangle neural interactions in the brain.…”
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Metal Oxide Nanomaterials as Rice Transgenic Carriers by Xiangbo Yang, Xia Bai, Zhenkai Zhang, Xiaoming Yu

“…In this paper, particle swarm optimization is used to optimize the weights of rice-growing convolutional neural networks. Secondly, it used rice as the test plant to study the effects of seven metal oxide nanomaterials on rice seed germination and root elongation. …”
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Authorship identification methods in student plagiarism detection by A. I. Paramonov, I. A. Trukhanovich

“…The advantages and limitations of each method are also discussed, and recommendations are given for choosing one or another approach according to the specific requirements of the research.Special attention is paid to such modern methods as metadata analysis and the application of neural networks. Stylistic analysis reveals authorial peculiarities such as word choice, preferred wording, and even punctuation. …”
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Deep Learning Based DDoS Attack Detection by Xu Ziyi

“…In order to improve detection accuracy and generalization, this research suggests a deep learning-based detection model that combines the Long Short-Term Memory (LSTM) network architecture with Convolutional Neural Networks (CNN). On the CICDDoS2019 dataset, which included several DDoS attack versions, the suggested model was trained and evaluated. …”
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Influence of proteinoids on calcium carbonate polymorphs precipitation in supersaturated solutions by Panagiotis Mougkogiannis, Andrew Adamatzky

“…We discuss the implications and applications of our work in the fields of bio-inspired computing, artificial neural networks, and origin of life research.…”
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